Optical detecting system

ABSTRACT

According to an embodiment of the present disclosure, provided is an optical detection system for detecting a laser speckle generated by multiple scattering of a wave irradiated toward a sample from a wave source, and based on a change in the laser speckle over time, detecting the presence of microbes in the sample in real time.

TECHNICAL FIELD

The present disclosure relates to an optical detection system fordetecting microbes or impurities.

BACKGROUND ART

Human beings coexist with other lifeforms. Invisible lifeforms, as wellas visible lifeforms, coexist with human beings, and directly/indirectlyaffect human lives. Among them, microbes or fine lifeforms affectinghealth states of human beings are not visible to human eyes, but existaround human beings and trigger various illnesses.

In order to measure invisible microbes, a microbe culture method, a massspectrometry method, a nuclear magnetic resonance method, etc. is usedaccording to the related art. When the microbe culture method, the massspectrometry method, and the nuclear magnetic resonance method are used,it takes a long time to culture bacteria and precise and complicatedequipment that is very expensive is necessary.

Alternately, a method of measuring microbes by using an optical methodmay be used. For example, a Raman spectrometry or a multispectralimaging method may be used as the optical method, but a complicatedoptical system is necessary, professional knowledge about thecomplicated optical system and laboratory level equipment are alsonecessary, and measurement takes a long time. Thus, it may be difficultfor the general public to access the system.

DESCRIPTION OF EMBODIMENTS Technical Problem

Provided is an optical detection system capable of detecting microbes orimpurities in real time by using a chaotic wave sensor.

Solution to Problem

According to an aspect of the present disclosure, an impurity detectionsystem includes: a pipe unit comprising a body portion formed with aninner space penetrating through a first cross section and a second crosssection such that a fluid introduced through the first cross section isdischarged through the second cross section and a multiple scatteringamplification region configured to amplify the number of times a firstwave incident between the first cross section and the second crosssection in a fluid located in the inner space is multiply scattered; awave source configured to irradiate the first wave toward the fluid ofthe pipe unit; a detector arranged outside the pipe unit and configuredto detect a laser speckle generated by multiple scattering of theirradiated first wave in the fluid for each preset first time and acontroller configured to obtain a temporal correlation of the detectedlaser speckle using the detected laser speckle and estimate the presenceof impurities in the fluid in real time based on the obtained temporalcorrelation, wherein one or more emission holes configured to guide asecond wave emitted by being multiply scattered in the fluid to thedetector are formed in the body portion of the pipe unit.

Advantageous Effects of Disclosure

The optical detection system according to embodiments of the presentdisclosure may use a variation in a temporal correlation of a laserspeckle, thereby estimating existence of impurities or concentration ofimpurities in a sample rapidly at low cost.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a diagram illustrating principles of a chaotic wave sensoraccording to an embodiment of the present disclosure.

FIG. 2 is a conceptual diagram schematically illustrating an impuritydetection system according to an embodiment of the present disclosure.

FIG. 3 is a cross-sectional view taken along a line II-II of FIG. 2.

FIG. 4 is a conceptual diagram schematically showing an impuritydetection system according to another embodiment of the presentdisclosure.

FIG. 5 is an absorbance diagram for each wavelength band when a fluid iswater.

FIGS. 6A and 6B are conceptual diagrams schematically showing animpurity detection system according to another embodiment of the presentdisclosure.

FIG. 7 is a conceptual diagram schematically showing a microbialpopulation counting system according to an embodiment of the presentdisclosure.

FIG. 8 is a cross-sectional view taken along a line III-III of FIG. 7.

FIG. 9 is a flowchart sequentially showing a method of counting amicrobial population according to an embodiment of the presentdisclosure.

FIGS. 10 and 11 are diagrams for explaining a method of counting amicrobial population.

FIG. 12 is a conceptual diagram schematically showing a microbialpopulation counting system according to another embodiment of thepresent disclosure.

FIG. 13 is a conceptual diagram schematically showing a sample placementunit according to another embodiment of the present disclosure.

FIG. 14 is a diagram schematically showing an airborne bacteriameasuring device according to an embodiment of the present disclosure.

FIG. 15 is a conceptual diagram for explaining the sampling principle ofthe airborne bacteria measuring device of FIG. 14.

FIG. 16 is a block diagram of the airborne bacteria measuring device ofFIG. 14.

FIGS. 17A to 17D are diagrams for explaining a process performed by theairborne bacteria measuring device of FIG. 14 of sampling bacteria andthen processing a collection liquid.

FIG. 18 is a diagram showing an example of a network environmentaccording to an embodiment of the present disclosure.

FIG. 19 is a block diagram schematically showing a server according toan embodiment of the present disclosure.

FIG. 20 is a diagram for describing a method, performed by a learner, ofanalyzing a temporal correlation of speckles according to an embodimentof the present disclosure.

FIG. 21 is a diagram showing a standard deviation distribution of thelight intensity of wave speckles measured over time.

FIG. 22 is a diagram showing a convolutional neural network (CNN)according to an embodiment of the present disclosure.

FIGS. 23 and 24 are diagrams for describing a convolution operation ofFIG. 22.

FIG. 25 is a graph comparing prediction microbe information (prediction)obtained by measuring airborne bacteria through machine learningaccording to an embodiment of the present disclosure and actual microbeinformation (ground truth).

FIG. 26 is a diagram schematically showing an optical detection systemaccording to an embodiment of the present disclosure.

FIG. 27 is a diagram for explaining a process, performed by a firstspeckle generation unit of generating a first speckle.

FIG. 28 is a diagram for explaining a process, performed by a secondspeckle generation unit of generating a second speckle.

FIG. 29 is a diagram for explaining a method, performed by a controllerof the present disclosure, of controlling an operation of a second imagesensor due to a first speckle.

FIG. 30 is a diagram schematically showing an optical detection systemof another embodiment.

FIG. 31 is a diagram schematically showing an optical detection systemaccording to another embodiment of the present disclosure.

FIGS. 32A and 32B are diagrams for explaining a method of determiningthe presence of live bacteria in a measurement sample using an opticaldetection system according to embodiments of the present disclosure.

BEST MODE

According to an aspect of the present disclosure, a pipe unit includes:a body portion comprising a first cross section, a second cross sectionfacing the first cross section, and an inner surface penetrating thefirst cross section and the second cross section to form an inner space,wherein the inner surface of the body portion comprises a multiplescattering amplification region in which a pattern for amplifying thenumber of times a first wave incident between the first cross sectionand the second cross section in a fluid located in the inner space ismultiply scattered is formed, and wherein the pattern is formed byarranging a plurality of grooves having a preset depth d from the innersurface at a preset interval A.

The depth d and the interval Λ of the pattern may be determined based onthe wavelength A of the first wave.

The depth d of the pattern may be determined to satisfy an equationbelow, wherein n is a refractive index of the fluid.

$\frac{\lambda}{2*n} \leq d$

The interval Λ of the pattern may be determined to satisfy an equationbelow, wherein θ denotes a scattering angle of the first wave scatteredby the pattern.

$\frac{1}{\Lambda} = \frac{\sin \; \theta}{\lambda}$

The body portion may include one or more emission holes configured toguide a second wave emitted by being multiple scattered in the fluid toa detector for detecting.

When two or more emission holes are formed, the two or more emissionholes may be disposed at different positions of the body portion.

According to another aspect of the present disclosure, an impuritydetection system includes: a pipe unit comprising a body portion formedwith an inner space penetrating through a first cross section and asecond cross section such that a fluid introduced through the firstcross section is discharged through the second cross section and amultiple scattering amplification region configured to amplify thenumber of times a first wave incident between the first cross sectionand the second cross section in a fluid located in the inner space ismultiply scattered; a wave source configured to irradiate the first wavetoward the fluid of the pipe unit; a detector disposed outside the pipeunit and configured to detect a laser speckle generated by multiplescattering the irradiated first wave in the fluid for each preset firsttime and a controller configured to obtain a temporal correlation of thedetected laser speckle using the detected laser speckle and estimate thepresence of impurities in the fluid in real time based on the obtainedtemporal correlation, wherein one or more emission holes configured toguide a second wave emitted by being multiple scattered in the fluid tothe detector are formed in the body portion of the pipe unit.

The body portion may include an inner surface surrounding the innerspace, the multiple scattering amplification region may be provided inthe inner surface of the body portion and formed with a pattern foramplifying the number of times the first wave is multiply scattered, andthe pattern may be formed by arranging a plurality of grooves having apreset depth d from the inner surface at a preset interval Λ.

The depth d and the interval Λ of the pattern may be determined based onthe wavelength λ of the first wave.

The depth d of the pattern may be determined to satisfy an equationbelow,

$\frac{\lambda}{2*n} \leq d$

wherein θ is a refractive index of the fluid.

The interval Λ of the pattern may be determined to satisfy an equationbelow,

$\frac{1}{\Lambda} = \frac{\sin \; \theta}{\lambda}$

wherein θ denotes a scattering angle of the first wave scattered by thepattern.

The second wave emitted from the one or more emission holes may have apower range of 1 mW/cm² or more in order for the detector to detect thelaser speckle at a preset measurement speed or more.

The measurement speed of the detector may be set such that a time forthe fluid to pass through the one or more emission holes is greater thana time between first times.

When two or more emission holes are formed, the two or more emissionholes may be disposed at different positions along a circumferentialdirection of the body portion, and the detector may be provided tocorrespond to the number of the two or more emission holes.

The first wave may have a wavelength range of 200 nm to 1.8 μm.

According to an aspect of the present disclosure, a microbial populationcounting method includes

providing a sample placement unit including a plurality of split cellseach including a culture material, distributing samples to be measuredto the plurality of split cells, irradiating waves sequentially to theplurality of split cells, sequentially detecting individual waveinformation emitted from samples includes in each split cell inassociation with the sequentially irradiated waves, determining thepresence of microbe in each split cell using the individual waveinformation, and calculating a microbial population in the sample usingthe number of split cells in which the microbe is present.

The individual wave information may be information obtained by detectinga laser speckle generated by multiple scattered from the sampleaccommodated in each of the plurality of split cells for each presettime.

The determining of the presence of the microbe may include obtaining atemporal correlation of the detected laser speckle using the detectedlaser speckle and determining the presence of the microbe in thecorresponding split cell based on the obtained temporal correlation.

The individual wave information may include first image information of alaser speckle detected at a first time, second image information of alaser speckle detected at a second time, and third image information ofa laser speckle detected at a third time among the laser speckle emittedfrom the corresponding split cell, wherein the first to third times aredifferent times, and the determining of the presence of the microbe mayinclude determining the presence of the microbe by using a differencebetween the first image information to the third image information.

The plurality of split cells may be arranged in the form of a matrix,and the number thereof may be greater than a predicted microbialpopulation included in the sample.

According to another aspect of the present disclosure, a microbialpopulation counting system includes a sample placement unit including aplurality of split cells each including a culture material, configuredto distribute and accommodate samples to be measured to the plurality ofsplit cells, a wave source configured to irradiate waves sequentially tothe plurality of split cells, a detector configured to sequentiallydetect individual wave information emitted from samples includes in eachsplit cell in association with the sequentially irradiated waves, and acontroller configured to determine the presence of microbe in each splitcell using the individual wave information and calculate a microbialpopulation in the sample using the number of split cells in which themicrobe is present.

The individual wave information may be information obtained by detectinga laser speckle generated by multiple scattered from the sampleaccommodated in each of the plurality of split cells for each presettime.

The controller may obtain a temporal correlation of the detected laserspeckle using the detected laser speckle and determine the presence ofthe microbe in the corresponding split cell based on the obtainedtemporal correlation.

The individual wave information may include first image information of alaser speckle detected at a first time, second image information of alaser speckle detected at a second time, and third image information ofa laser speckle detected at a third time among the laser speckle emittedfrom the corresponding split cell, wherein the first to third times aredifferent times, and the controller may determine the presence of themicrobe by using a difference between the first image information to thethird image information.

The plurality of split cells may be arranged in the form of a matrix,and the number thereof may be greater than a predicted microbialpopulation included in the sample.

According to another aspect of the present disclosure, an airbornebacteria measuring device includes a collection unit including a storagetank configured to accommodate a collection liquid therein, aninhalation flow path configured to inhale external air to guide anexternal air to the collection liquid in one side of the storage tank,and an exhaust flow path configured to discharge the air of the storagetank to the outside in the other side of the storage tank, a wave sourceconfigured to irradiate a wave toward the collection liquid of thecollection unit, an image sensor configured to time serially measure awave speckle generated by multiple scattering the wave in the collectionliquid, and a controller configured to detect the presence of microbe inthe collection liquid according to a change in the measured wave speckleover time.

The controller may obtain a temporal correlation of the wave speckle anddetect the presence of the microbe in the collection liquid based on theobtained temporal correlation.

The collection unit may further include a collection liquid dischargepipe configured to discharge the completely detected collection liquidand a collection liquid flow pipe configured to flow a new collectionliquid into the storage tank.

The airborne bacteria measuring device may further include a first valveinstalled in the collection liquid flow pipe and selectively opening andclosing the collection liquid flow pipe and a second valve installed inthe collection liquid discharge pipe and selectively opening and closingthe collection liquid discharge pipe, and the controller may control anoperation of the first valve or the second valve by a preset program.

The airborne bacteria measuring device may further include asterilization unit configured to sterilize the completely detectedcollection liquid in the storage tank, and the controller may control anoperation of the second valve to discharge the collection liquid after asterilization process of the collection liquid is completed.

The airborne bacteria measuring device may further include a filter unitinstalled in the inhalation flow path and configured to filter asubstance having a predetermined size or more included in the externalair introduced into the inhalation flow path.

The collection unit may further include a multiple scattering amplifierconfigured to reflect at least a part of the wave emitted from thecollection liquid to the collection liquid to amplify the number oftimes of multiple scattering in the collection liquid.

The controller may identify a type or concentration of microbe presentin the collection liquid based on a change in the wave speckle overtime.

The controller may learn a microbial classification criteria based onthe change of the wave speckle over time measured in time series order,and identify the type or concentration of microbe present in thecollection liquid using the microbial classification criteria.

According to another aspect of the present disclosure, an opticaldetection system includes a wave source, an optical unit configured totransferring a wave generated in the wave source to a first path or asecond path, a first speckle generation unit disposed on the first pathand including a static scattering medium to scatter the first waveincident along the first path and generate a first speckle, a firstimage sensor configured to detect the first speckle in time seriesorder, a sample accommodation unit disposed on the second path andincluding a sample to be measured, a second image sensor configured todetect an optical signal generated in the sample in time series order,and a controller configured to obtain a temporal correlation of thefirst speckle using the detected first speckle and control an operationof the second image sensor based on the obtained temporal correlation ofthe first speckle.

The sample accommodation unit may include a second speckle generationunit configured to scatter a second wave incident along the second pathand generate a second speckle.

The controller may obtain a temporal correlation of the second speckledetected using the detected second speckle, and estimate the presence orconcentration of microbe in the sample based on the obtained temporalcorrelation of the second speckle.

The controller may determine a change in the property of the first wavebased on the temporal correlation of the first speckle, and control anoperation of the second image sensor according to the change in theproperty of the first wave.

The controller may calculate a temporal correlation coefficient of thefirst speckle and operate the second image sensor only when the temporalcorrelation coefficient of the first speckle corresponds to a presetrange.

The controller may calculate the temporal correlation coefficient of thefirst speckle and use the temporal correlation coefficient of the firstspeckle to calibrate a detection signal of the second image sensor.

The first speckle generation unit and the second speckle generation unitmay be integrally formed.

The second speckle generation unit may further include a multiplescattering amplifier including a multiple scattering material to amplifythe number of times of multiple scattering of the second wave in thesample.

According to another aspect of the present disclosure, an opticaldetection system includes a wave source, an optical unit configured totransferring a wave generated in the wave source to a first path or asecond path, a first speckle generation unit disposed on the first pathand including a static scattering medium to scatter the first waveincident along the first path and generate a first speckle, a secondgeneration unit disposed on the second path and including a sample to bemeasured to scatter a second wave incident along the second path andgenerate a second speckle, a second shutter disposed between the firstoptical unit and the second speckle generation unit, an image sensorconfigured to detect the first speckle or the second speckle in timeseries order, and a controller configured to obtain a temporalcorrelation of the first speckle using the detected first speckle by theimage sensor and control an operation of the second shutter based on theobtained temporal correlation of the first speckle.

The controller may obtain a temporal correlation of the second speckledetected using the detected second speckle, and estimate the presence orconcentration of microbe in the sample based on the obtained temporalcorrelation of the second speckle.

The controller may determine a change in the property of the first wavebased on the temporal correlation of the first speckle, and control anoperation of the second shutter according to the change in the propertyof the first wave.

The controller may calculate a temporal correlation coefficient of thefirst speckle and open the second shutter to detect the second speckleonly when the temporal correlation coefficient of the first specklecorresponds to a preset range.

The optical detection system may further include a first shutterdisposed between the first optical unit and the first speckle generationunit, and the controller may control the first shutter to be closedwhile the second shutter is opened.

The second speckle generation unit may further include a multiplescattering amplifier including a multiple scattering material to amplifythe number of times of multiple scattering of the second wave in thesample.

According to another aspect of the present disclosure, an opticaldetection system includes a wave source, an optical unit configured totransferring a wave generated in the wave source to a first path or asecond path, a first speckle generation unit disposed on the first pathand including a control group sample to scatter the first wave incidentalong the first path and generate a first speckle, a first image sensorconfigured to detect the first speckle in time series order, a secondgeneration unit disposed on the second path and including a measurementgroup sample and a medium to scatter a second wave incident along thesecond path and generate a second speckle, a second image sensorconfigured to detect the second speckle in time series order, and acontroller configured to estimate a first concentration of the controlgroup sample and a second concentration of the measurement group sampleusing the detected first speckle and the detected second speckle, anddetermine the presence of live bacteria in the measurement group sampleusing the first concentration and the second concentration.

The controller may obtain a temporal correlation of the first speckledetected using the detected first speckle, and then estimate the firstconcentration of the control group sample using the temporal correlationof the first speckle, obtain a temporal correlation of the secondspeckle detected using the detected second speckle, and then estimatethe second concentration of the measurement group sample using thetemporal correlation of the second speckle.

The measurement group sample may be a sample diluted m times the controlgroup sample, and the controller may obtain a growth time at which thesecond concentration is equal to the first concentration and then derivea ratio of live bacteria and dead bacteria in the measurement groupsample using the growth time.

The second speckle generation unit may further include a multiplescattering amplifier including a multiple scattering material to amplifythe number of times of multiple scattering of the second wave in thesample.

Other aspects, features and advantages of the present disclosure willbecome better understood through the accompanying drawings, the claimsand the detailed description.

MODE OF DISCLOSURE

The exemplary embodiments will be described below in more detail withreference to the accompanying drawings. Those components that are thesame or are in correspondence are rendered the same reference numeralregardless of the figure number, and redundant explanations are omitted.

As the present disclosure allows for various changes and numerousembodiments, particular embodiments will be illustrated in the drawingsand described in detail in the written description. The attacheddrawings for illustrating one or more embodiments are referred to inorder to gain a sufficient understanding, the merits thereof, and theobjectives accomplished by the implementation. However, the embodimentsmay have different forms and should not be construed as being limited tothe descriptions set forth herein.

While such terms as “first,” “second,” etc., may be used to describevarious components, such components must not be limited to the aboveterms. The above terms are used only to distinguish one component fromanother.

An expression used in the singular encompasses the expression of theplural, unless it has a clearly different meaning in the context.

In the present specification, it is to be understood that the terms suchas “including,” “having,” and “comprising” are intended to indicate theexistence of the features or components disclosed in the specification,and are not intended to preclude the possibility that one or more otherfeatures or components may exist or may be added.

It will be understood that when a unit, region, or component is referredto as being “formed on” another layer, region, or component, it can bedirectly or indirectly formed on the other layer, region, or component.That is, for example, intervening units, regions, or components may bepresent.

It will be understood that when an element is referred to as being“connected” or “coupled” to another element, it does necessarily notmean direct and/or fixed connection or coupling of to the two elementsor intervening elements may be present, unless it has a clearlydifferent meaning in the context.

It will be further understood that the terms “comprises,” “comprising,”“includes” and/or “including,” when used herein, specify the presence ofstated features or components, but do not preclude the presence oraddition of one or more other features or components.

Sizes of components in the drawings may be exaggerated for convenienceof explanation. In other words, since sizes and thicknesses ofcomponents in the drawings are arbitrarily illustrated for convenienceof explanation, the following embodiments are not limited thereto.

Hereinafter, principles of a chaotic wave sensor according to anembodiment of the present disclosure will be described with reference toFIG. 1.

FIG. 1 is a diagram illustrating principles of a chaotic wave sensoraccording to an embodiment of the present disclosure.

When light is irradiated to a material having a uniform internalrefractive index, e.g., glass, the light is refracted in a constantdirection. However, when coherent light such as a laser is irradiated toa material having a non-uniform internal refractive index, multiplescattering that is very complicated occurs in the material.

Referring to FIG. 1, in light or waves (hereinafter, referred to aswaves for convenience's sake) irradiated from a wave source 120, some ofthe waves scatter through complicated paths due to the multiplescattering pass through a test target surface. Waves passing throughmultiple points in the test target surface generate constructiveinterference or destructive interference, and theconstructive/destructive interference of the waves generates grainpatterns (speckles).

In the present specification, the waves scattered in the complicatedpaths are referred to as “chaotic wave”, and the chaotic wave may bedetected through laser speckles.

The left side of FIG. 1 shows a state in which a laser is irradiated toa stabilized medium. When interference light (e.g., laser) is irradiatedto the stabilized medium, in which internal component material does notmove, a stabilized speckle pattern without a variation may be observed.

However, as shown at the right side of FIG. 1, when the medium has anon-stabilized internal component that is moving, such as bacteria, thespeckle pattern varies.

That is, fine activity of life, e.g., movement of microbes, may finelychange an optical path according to time. Since the speckle pattern isgenerated due to interference of the waves, a fine change in the opticalpath may cause variation in the speckle pattern. Accordingly, when atemporal variation in the speckle pattern is measured, the activities ofmicrobes may be rapidly measured. As described above, when the variationin the speckle pattern according to time is measured, existence of themicrobes and concentration of the microbes may be identified, andfurther, kinds of the microbes may be identified.

In the present specification, a structure for measuring the variation inthe speckle pattern is defined as a chaotic wave sensor.

In the present specification, embodiments of an optical detection systemhaving various applications such as technology of detecting impuritiesin a fluid, technology of counting microbial population, airbornebacteria measuring technology and wave correction technology whilehaving a basic idea of detecting microbe or impurities present in astatic medium by using the chaotic wave sensor as described above willbe described. At this time, the optical detection system may be called adifferent name for each embodiment, and may be designated with adifferent name or numeral for the convenience of description even if itincludes components that perform the same function. Here, the medium maybe applied to any material or state having a static property.

FIG. 2 is a conceptual diagram schematically illustrating an impuritydetection system 10 according to an embodiment of the presentdisclosure, and FIG. 3 is a cross-sectional view taken along line II-IIof FIG. 2. FIG. 4 is a conceptual diagram schematically showing animpurity detection system 10′ according to another embodiment of thepresent disclosure.

Referring to FIGS. 2 and 3, an impurity detection system 10 in a fluidaccording to an embodiment of the present disclosure may include a pipeunit 1110, a wave source 1200, a detector 1300, and a controller 1400.

The pipe unit 1110 may include a first cross section A11 and a secondcross section A21, and may include a body portion 1100 including aninner surface 1101 penetrating the first cross section A11 and thesecond cross section A21 to form an inner space. In this case, the firstcross section A11 and the second cross section A21 may be disposed toface each other. The body portion 1100 may be formed, for example, in acylindrical shape, but the present disclosure is not limited thereto.

A fluid may be introduced through the second cross section A21 of thepipe unit 1110 and may be discharged through the first cross section A11via the inner space. In the present specification, the fluid may be aliquid or a gas, and may have a preset flow rate. The pipe unit 1110 maybe disposed at any part of a production line of liquid such as bottledwater or beverage, and the fluid may be introduced through the secondcross section A21 to penetrate the inner space of the pipe unit 1110 andthen may be discharged through the first cross section A11. For example,the flow rate of the fluid may range from 4 m/s to 5 m/s, which is aflow rate of an actual factory environment. However, the presentdisclosure is not limited thereto, and the flow rate of the fluid mayhave a flow rate of 1 m/s or less like a water pipe.

As another example, the flow rate of the fluid may be set based on themeasurement conditions in the detector 1300. In other words, even if theflow rate of the actual factory environment is 4 m/s to 5 m/s, theimpurity detection system 10 may reduce the flow rate of the fluid to apreset rate such that the flow rate of the fluid immediately before thepipe unit 1110 is a rate measurable by the detector 1300.

As used herein, an impurity may be a material of a small size, such as amicrobe, that exceeds the visual limit of the human eye. In anembodiment, when the impurity is a microbe, the fluid may be a materialto which the microbe may proliferate, for example, water that does notinclude a scattering material therein. However, the present disclosureis not limited thereto, and in another embodiment, the fluid may be amaterial such as milk including the scattering material therein. Inanother embodiment, the fluid may also be air.

Although not shown, the fluid may be introduced into the pipe unit 1110through a fluid supply unit. The fluid supply unit may include a fluidstorage tank and a supply means such as a hydraulic pump or a compressorfor providing a flow force to the fluid include in the fluid storagetank. The fluid may pass through the pipe unit 1110 in one directionthrough the supply means.

In an embodiment, the pipe unit 1110 may introduce the fluid through theentire area of the second cross section A21, and discharge the fluidthrough the entire area of the first cross section A11. In other words,the fluid may move in a state in which the inside of the pipe unit 1110is filled up. When the fluid moves in a state where the cross-sectionalarea of the pipe unit 1110 is not 100% filled, a wavefront may begenerated in the fluid due to the flow of the fluid. Such a wavefrontmay act as a scatterer, and may act as a noise to detect impuritiesthrough the detector 1300. Accordingly, in order to minimize such noise,the pipe unit 1110 may discharge the fluid through the entire areas ofthe first cross section A11 and the second cross section A21.

Meanwhile, the body portion 1100 of the pipe unit 1110 may include amultiple scattering amplification region MSA1 formed on an inner surface1101. A pattern for amplifying the number of times of multiplescattering of a first wave L11 incident between the first cross sectionA11 and the second cross section A21 in the fluid located in the innerspace of the pipe unit 1110 may be formed in the multiple scatteringamplification region MSA1.

The multiple scattering amplification region MSA1 may scatter at least apart of the first wave L11 that is incident into the inner space of thepipe unit 1110 and passes through the fluid and is emitted toward theinner surface 1101 into the fluid again. The first wave L11 scattered asdescribed above may be emitted to the other side of the inner surface1101 through the fluid and scattered, and through this process, thenumber of times of multiple scattering in the fluid may increase. Inthis case, the multiple scattering amplifier region MSA1 may amplify thenumber of multiple scattering due to patterns formed based on awavelength A of the incident first wave L11.

The pattern may include a plurality of grooves g formed in a concaveshape from the inner surface 1101 toward an outer surface of the pipeunit 1110. The pattern may be formed by arranging the plurality ofgrooves g having a preset depth d from the inner surface 1101 at apreset interval A. Here, the depth d and the interval Λ of the patternmay be determined based on the wavelength A of the first wave.

Specifically, the depth d of the pattern may be determined to satisfyEquation 1 below,

$\begin{matrix}{\frac{\lambda}{2*n} \leq d} & \left\lbrack {{Equation}\mspace{14mu} 1} \right\rbrack\end{matrix}$

wherein n may be a refractive index of the fluid passing through theinner space of the pipe unit 1110. When the depth d of the pattern issmaller than

$\frac{\lambda}{2*n},$

the first wave L11 incident on the inner surface 1101 has a highreflectance, making it difficult to increase the intended number oftimes of multiple scattering. The pipe unit 1110 may increase ascattering rate in the inner space by forming the pattern to satisfyEquation 1 above. In addition, the depths d of the pattern including theplurality of grooves g may not need to be the same, and even if they areformed irregularly, if the depth d of each of the grooves g satisfiesthe above Expression 1, a sufficient scattering rate may be secured. Inthis case, the depth d of the pattern may not exceed the cross-sectionalthickness of the pipe unit 1110.

In addition, the interval Λ of the pattern may be determined to satisfyEquation 2 below,

$\begin{matrix}{\frac{1}{\Lambda} = \frac{\sin \; \theta}{\lambda}} & \left\lbrack {{Equation}\mspace{14mu} 2} \right\rbrack\end{matrix}$

wherein θ may denote a scattering angle of the first wave L11 scatteredby the pattern. In addition, the interval Λ of the grooves g may be aninterval between peaks of unevennesses formed by the grooves g. Thescattering angle θ may be determined according to an area of themultiple scattering amplification region MSA1 and/or power of the firstwave L11. When the scattering angle θ is large, the first wave L11 maybe scattered over a larger area than that when the scattering angle θ issmall, whereas the power of the first wave L11 after scattered may bereduced rather than when the scattering angle θ is small. Using thisrelationship, the scattering angle θ may be determined according to themeasurement conditions, for example, a diameter R1 of the pipe unit 1110or the power of the first wave L11 emitted from the wave source 1200.

Meanwhile, the pattern may include the plurality of grooves g arrangedin a predetermined direction. In an embodiment, as shown in the drawing,the pattern may be formed by arranging the grooves g extending in adirection perpendicular to a longitudinal direction of the pipe unit1110 at the interval A. In another embodiment, although not shown, thepattern may be formed by arranging the grooves g extending in thelongitudinal direction of the pipe unit 1110 at the interval A. Inanother embodiment, the pattern may include first grooves extending andarranged along the longitudinal direction of the pipe unit 1110 andsecond grooves formed to overlapping the first grooves and extending andarranged in the direction perpendicular to the longitudinal direction ofthe pipe unit 1110.

In this case, the multiple scattering amplification region MSA1 may beconfigured in a pattern formed in a lattice form. When the plurality ofgrooves g extending along the circumferential direction are arrangedalong the longitudinal direction of the pipe unit 1110, the incidentfirst wave L11 is different depending on an incident angle, but theincident first wave L11 is mostly scattered in the longitudinaldirection of the pipe unit 1110. In addition, when the plurality ofgrooves g extending in the longitudinal direction are arranged along thecircumferential direction of the pipe unit 1110, the incident first waveL11 is mostly scattered in the circumferential direction of the pipeunit 1110. In other words, in the case where the first wave L11 isscattered to amplify the number of times of multiple scattering to thecross-section of the pipe unit 1110, the grooves g may be formed to bearranged along the circumferential direction, and in the case where thenumber of multiple scattering is amplified in the longitudinal directionof the pipe unit 1110, the grooves g may be formed to be arranged alongthe longitudinal direction. In addition, because the number of times ofmultiple scattering is amplified in various directions by forming thepattern in grooves crossing in different directions, the cross-sectionand the longitudinal direction of the pipe unit 1110 may be closelyfilled with the first wave L11. Through this, the impurity detectionsystem 10 may increase a probability of detecting impurities in thefluid.

Meanwhile, in another embodiment, the multiple scattering amplificationregion MSA1 may include a multiple scattering material. For example, themultiple scattering material may include particles having a diameter ofa micrometer having a large refractive index or less, for example,titanium oxide (TiO₂) nanoparticles. In this case, the multiplescattering amplification region MSA1 may be formed by coating themultiple scattering material on an outer surface of a main body of thepipe unit 1110. However, the present disclosure is not limited thereto,and in another embodiment, the multiple scattering amplification regionMSA1 may be formed by including the multiple scattering material in themain body of the pipe unit 1110. Alternatively, in the case of an opaquepipe such as a metal pipe, the multiple scattering amplification regionMSA1 may be formed by coating a multiple scattering material on an innersurface of the main body of the pipe unit 1110.

In another embodiment, the multiple scattering amplification region MSA1may include a multiple scattering amplifier (not shown) disposedadjacent to the main body of the pipe unit 1110 to reflect at least apart of wave emitted from the fluid to the outside of the pipe unit 1110to the inside of the pipe unit 1110. In this case, the multiplescattering amplifier (not shown) may cause the wave emitted from thepipe unit 1110 to reciprocate a space between the pipe unit 1110 and themultiple scattering amplifier (not shown) at least one or more times.Meanwhile, the multiple scattering amplification region MSA1 may bedisposed in at least a partial region between the first cross sectionA11 and the second cross section A21 of the pipe unit 1110, for example,in the entire region.

Meanwhile, at least a part of the multiple scattering amplificationregion MSA1 may be a reflection region 1105 reflecting the entirety ofthe first wave L11 emitted from the fluid into the fluid. The reflectionregion 1105 may increase the impurity detection rate of the detector1300 by minimizing the emission of the first wave L11 from the fluid tothe outside of the pipe unit 1110. The reflection region 1105 may bedisposed to face an incident region where the first wave L11 is incidentfrom the wave source 1200. The reflection region 1105 may reflect theentirety of the first wave L11 irradiated from the wave source 1200 intothe fluid, thereby increasing an amount of waves capable of beingmultiple scattered in the fluid, and accordingly amplifying the impuritydetection rate in the detector 1300. In another embodiment, the entireregion of the multiple scattering amplification region MSA1 except foran emission hole 1103 may be a reflection region.

Meanwhile, the pipe unit 1110 may include one or more emission holes1103 guiding a second wave emitted by being multiple scattered in thefluid to the detector 1300 for detecting. The detector 1300, which willbe described later, may be disposed adjacent to the emission hole 1103to detect the second wave L21 emitted from the emission hole 1103. Theemission hole 1103 may be configured as a hole penetrating the bodyportion 1100 as shown.

At this time, as shown, the pipe unit 1110 may further include a coverportion 1109 disposed at one side of the emission hole 1103. The coverportion 1109 may include a transparent or translucent material such thatthe second wave L21 may pass therethrough. For example, the coverportion 1109 may include a glass or plastic material, and may be formedin a plate shape having flexibility, but may also be manufactured in afilm. In another embodiment, the cover portion 1109 may be formed tofill the inside of the emission hole 1103 rather than one side of theemission hole 1103.

Meanwhile, although in the drawing exaggerated for convenience ofexplanation, the emission hole 1103 may have a minimum diameter R2 bywhich the second wave L21 may be emitted while ensuring the scatteringrate in the inner space of the pipe unit 1110 to the maximum.

Meanwhile, referring to FIG. 4, two or more emission holes 1103 may beformed in the body portion 1100 of the pipe unit 1110. When two or moreemission holes 1103 are formed, the two or more emission holes 1103 maybe disposed at different positions along the circumferential directionof the body portion 1100. Through this structure, the plurality ofsecond waves L21 may be guided to a plurality of detectors 31, 33, and35 that will be described later.

Hereinafter, the impurity detection system 10 including the pipe unit1110 described above will be described in more detail.

Because a fluid such as water does not include a homogeneous substancethat causes scattering therein as described above, a laser speckle maynot be generated when a microbe M, which is an impurity, is not present.However, the system 10 for detecting the microbe M in a fluid accordingto an embodiment of the present disclosure may multiple scatter thefirst wave through the multiple scattering amplification region MSA1 ofthe pipe unit 1110 described above to generate a static laser specklepattern. The system 10 for detecting the microbe M in the fluid L maychange a path of the first wave by a movement of the microbe M when themicrobe M is present in the fluid L that moves in the pipe unit 1110. Asubtle change in a first wave path may cause a change in the specklepattern. Accordingly, by measuring a temporal change of the specklepattern, the presence of the microbe M in the fluid L may be rapidlydetected.

Referring to FIGS. 2 and 3 again, the wave source 1200 may irradiate thefirst wave L11 toward the fluid of the pipe unit 1110. The wave source1200 may apply all types of source device capable of generating a wave,and may be, for example, a laser capable of irradiating light of aspecific wavelength band. Although the present disclosure is not limitedto a type of a wave source, a case where the wave source is the laserwill be described for convenience of description.

For example, laser with a good coherence may be used as the wave source1200 to form speckle in the fluid. In this case, the shorter thespectral bandwidth of the wave source that determines the coherence ofthe laser wave source, the greater the measurement accuracy. That is,the longer the coherence length, the greater the measurement accuracy.Accordingly, a laser light whose spectral bandwidth of the wave sourceis less than a predetermined reference bandwidth may be used as the wavesource 1200, and the measurement accuracy may increase as the spectralbandwidth of the wave source is shorter than the reference bandwidth.For example, the spectral bandwidth of the wave source may be set suchthat the condition of Equation 3 below is maintained.

spectralbandwidth<5 nm  [Equation 3]

According to Equation 3, in order to measure the pattern change of thelaser speckle, the spectral bandwidth of the wave source 1200 may bemaintained less than 5 nm when light is irradiated into the fluid everyreference time.

In an embodiment, the wave source 1200 may be disposed outside the pipeunit 1110 to irradiate the first wave L11 toward the pipe unit 1110 asshown. In this case, an incidence hole (not shown) penetrating the bodyportion 1100 may be formed in the pipe unit 1110 to transmit the firstwave L11 radiated from the wave source 1200 to the fluid. The incidencehole (not shown) may be formed to have the same diameter as the emissionhole 1103 described above, and the cover portion 1109 may be disposedlike the emission hole 1103. In another embodiment, the wave source 1200may be disposed in the inner surface of the pipe unit 1110 or may beembedded in the body portion 1100 of the pipe unit 1110 to irradiate thefirst wave L11 toward the fluid. In the drawing, the wave source 1200 isillustrated as one, but a plurality of wave sources 1200 may be providedas necessary.

Meanwhile, the wave source 1200 may output the first wave L11 having apredetermined first power and the wavelength A.

FIG. 5 is an absorbance diagram for each wavelength band when a fluid iswater.

Referring to FIG. 5, the first wave L11 may have the wavelength A in therange of a first wavelength λ1 to a second wavelength A2. The fluid mayabsorb waves. Absorbance generally means that the energy of photons,such as electrons in an atom, is absorbed by a material, and the energyof such waves may be converted into the internal energy of the fluid,such as thermal energy. As the absorption occurs more, the fluidinternal temperature increases, and the power of the first wave L11decreases as much as the fluid internal temperature increases. If adegree of the power reduction of the first wave L11 is large whilepassing through the fluid, detection by the detector 1300 may bedifficult.

Because the absorption in the fluid is different for each wavelengthband as shown in FIG. 5, the first wave L11 may be set to have awavelength range that may minimize absorption in the fluid. For example,when the fluid is water, the fluid may have an absorption coefficientfor each wavelength band as shown in FIG. 5. The impurity detectionsystem 10 according to an embodiment of the present disclosure may usethe first wave L11 having a wavelength range in which the absorptioncoefficient of the fluid is equal to or less than a predetermined valuein order to minimize absorption of waves in the fluid. For example, thefirst wave L11 may have a wavelength range of 200 nm to 1.8 mm such thatan absorption coefficient of water has a value less than 1×10³ to 1×10⁴.

Referring to FIGS. 2 and 3 again, the detector 1300 may detect a laserspeckle generated by multiple scattering the irradiated first wave L11in the fluid for each preset time. Here, time means any moment in acontinuous flow of time, and times may be set in advance at the sametime interval, but are not limited thereto, and may be set in advance atany time interval.

The detector 1300 may include a sensing means corresponding to a type ofthe wave source 1200. For example, when a light source of a visiblelight wavelength band is used, a CCD camera which is an image capturingdevice may be used. The detector 1300 may detect a laser speckle atleast at a first time, detect a laser speckle at a second time, andprovide the detected laser speckles to the controller 1400. Meanwhile,the first point and the second time are merely one example selected forconvenience of description, and the detector 1300 may detect laserspeckles at a plurality of times more than the first point and thesecond time.

Specifically, when the first wave L11 is irradiated to the fluid, theincident first wave L11 may form a laser speckle by multiple scattering.Because the laser speckle is generated by the interference of light, ifthere is no microbe in the fluid, a multiple scattering amplificationregion may always show a constant interference pattern over time. Incomparison, when the microbe M is present in the fluid, the laserspeckle may change over time by a movement of the microbe M. Thedetector 1300 may detect the laser speckle that changes over time foreach preset time and provide the laser speckle to the controller 1400.The detector 1300 may detect the laser speckle at a speed sufficient todetect the movement of the microbe M, and for example, may detect thelaser speckle at the speed of 25 to 30 frames per second.

The detector 1300 may be disposed adjacent to the emission hole 1103 ofthe pipe unit 1110, and detect the second wave L21 emitted through theemission hole 1103 after the first wave L11 irradiated from the wavesource 1200 is multiply scattered. In this case, the second wave L21 mayhave a power range of 1 mW/cm² or more such that the detector 1300 maydetect the laser speckle at a measurement speed greater than or equal toa preset measurement speed. When the second power of the second wave L21is smaller than 1 mW/cm², the detector 1300 which measures rapidly maynot sufficiently detect the second wave L21. In addition, the detector1300 should be capable of high speed measurement in order to detect themicrobe M which is an impurity from the flowing fluid. Here, high speedmeasurement means detecting a laser speckle faster than a flow rate ofthe fluid. For example, the measurement speed of the detector 1300 maybe set such that a time T1 at which the fluid passes the emission hole1103 is greater than a time T2 between the first times for detecting thelaser speckle.

$\frac{T\; 1}{T\; 2} > 1$

Meanwhile, the first wave L11 irradiated from the wave source 1200 hasthe first power, and the second wave L21 that is multiply scattered andemitted from the pipe unit 1110 has the second power. Ideally, the firstpower of the first wave L11 and the second power of the second wave L21are equal to each other, and the wave source 1200 may irradiate waveswith power of 1 mW/cm² or more but the first power of the first wave L11is significantly reduced in a multiple scattering process. Therefore,the second power of the second wave L21 may be smaller than the firstpower of the first wave L11. The second power of the second wave L21 maybe different according to the diameter R1 of the pipe unit 1110, thefirst power magnitude of the first wave L11, a degree of absorption ofthe fluid with respect to a wavelength of the first wave L11 and adiameter R2 of the emission hole 1103. For example, the second power ofthe second wave L21 may be proportional to the first power of the firstwave L11, inversely proportional to the diameter R1 of the pipe unit1110, and proportional to the diameter R2 of the emission hole 1103.

Meanwhile, when an image sensor is used as the detector 1300, the imagesensor may be disposed such that a size d of one pixel of the imagesensor is smaller than or equal to a grain size of a speckle pattern.For example, the image sensor may be disposed in an optical systemincluded in the detector 300 to satisfy the condition of Equation 4below.

d≤speckle grain size  [Equation 4]

As shown in Equation 4, the size d of one pixel of the image sensorshould be less than or equal to the grain size of the speckle pattern.However, if the size of the pixel becomes too small, undersampling mayoccur and there may be difficulties in utilizing pixel resolution.Accordingly, the image sensor may be disposed such that a maximum offive pixels or less are positioned at a speckle grain size to achieve aneffective signal to noise ratio (SNR).

The controller 1400 may obtain a temporal correlation of the detectedlaser speckles using the detected laser speckles. The controller 1400may estimate the presence of impurities in the fluid in real time basedon the obtained temporal correlation. Real time in the presentspecification means estimating the presence of the microbe M within 3seconds, preferably, it is possible to estimate the presence of themicrobe M within 1 second.

In an embodiment, the controller 1400 may use a difference between firstimage information of the laser speckle detected at the first time andsecond image information of a second laser speckle detected at thesecond time to estimate the presence of the microbe M. Here, the firstimage information and the second image information may be at least oneof pattern information of the laser speckle and intensity information ofwaves. Meanwhile, an embodiment of the present disclosure does not useonly the difference between the first image information at the firsttime and the second image information at the second time but may extendthis to use image information of a plurality of laser speckles at aplurality of times. The controller 1400 may calculate a temporalcorrelation coefficient between images using image information of laserspeckles generated for a plurality of preset times, and estimate thepresence of the microbe M in the fluid based on the temporal correlationcoefficient. The detected temporal correlation of the laser speckleimages may be calculated using Equation 5 below.

$\begin{matrix}{{\overset{\_}{C}\left( {x,{y;\tau}} \right)} = {\frac{1}{T - \tau}{\sum\limits_{t = 1}^{T - \tau}\; {{\overset{\_}{I}\left( {x,{y;\tau}} \right)}{\overset{\_}{I}\left( {x,{y;{t + \tau}}} \right)}\delta \; t}}}} & \left\lbrack {{Equation}\mspace{14mu} 5} \right\rbrack\end{matrix}$

In Equation 5, C denotes the temporal correlation coefficient, Ī denotesnormalized light intensity, (x, y) denotes a pixel coordinate of acamera, t denotes a measured time, T denotes a total measurement time,and τ denotes a time lag.

The temporal correlation coefficient may be calculated according toEquation 5, and in an embodiment, the presence of the microbe may beestimated through an analysis in which the temporal correlationcoefficient falls below a preset reference value. Specifically, it maybe estimated that the microbe is present from that the temporalcorrelation coefficient falls below the reference value exceeding apreset error range.

Referring to FIG. 3 again, in another embodiment, the impurity detectionsystem 10′ may include a plurality of detectors 1310, 1330, and 1350. Asdescribed above, a plurality of emission holes 1103 may be formed in thebody portion 1100 of the pipe unit 1110, and the detectors 1300 may bepositioned at positions corresponding to the respective emission holes1103.

The first wave L11 irradiated to the pipe unit 1110 may be multiplyscattered in the fluid and then emitted through the emission hole 1103,and the second power of the emitted second wave L21 may be differentaccording to the position of the emission hole 1103. The first wave L11irradiated to the pipe unit 1110 is scattered according to the intervalΛ and the depth d of the pattern in the multiple scatteringamplification region MSA1. The pattern has irregularity due totolerances or intentional patterning in a manufacturing process.Accordingly, the first wave L11 is not scattered regularly in the fluidof the multiple scattering amplification region MSA1 but is scatteredirregularly, and the second power of the second wave L21 may bedifferent according to the emission position. The impurity detectionsystem 10′ according to another embodiment of the present disclosuredetects the laser speckle of the second wave L21 emitted by using theplurality of detectors 1310, 1330, and 1350 disposed at differentpositions, and thus a stable impurity detection is possible.

Specifically, the plurality of detectors 1310, 1330, and 1350 may detectthe second wave L21 having different second powers. For example, thefirst detector 1310 may detect the second wave L21 having a 2-1th power,the second detector 1330 may detect the second wave L21 having a 2-2thpower, and the third detector 1350 may detect the second wave L21 havinga 2-3th power. The 2-1th power, the 2-2th power, and the 2-3th power mayhave different values. Ideally, because the irradiated first wave L11 ismultiply scattered in the pipe unit 1110 in various directions and fillsup the cross-section of the pipe unit 1110, the microbe M of a fine sizemay be effectively detected regardless of which direction the laserspeckle is detected.

However, in an actual detection environment, the power of the emittedsecond wave L21 may be different according to the position due tofactors such as a pattern degree of the pipe unit 1110 or a flow rate ofthe fluid. If only the first detector 1310 is provided, the second waveL21 of the 2-1th power is detected. In this case, a positioncorresponding to the first detector 1310 may be a shade region of thesecond wave L21, which may reduce detection power. The impuritydetection system 10′ may include a plurality of emission holes 1103, andthe plurality of detectors 1310, 1330, and 1350 disposed in variousdirections, and thus complementary detection may be possible. Thecontroller 1400 may detect impurities using values detected by the firstto third detectors 1310, 1330, and 1350. For example, the controller1400 may average information of laser speckles detected by the first tothird detectors 1310, 1330, and 1350 and utilize the information todetect impurities.

In this case, when there are two or more emission holes 1103, theemission holes 1103 may be disposed at different positions of the bodyportion 1100, and the detectors 1310, 1330, and 1350 may be provided tocorrespond to the number of emission holes 1103. The impurity detectionsystem 10′ may allow the detectors 1310, 1330, and 1350 to be disposedat different positions on the same circumference, and thus when theimpurity microbe M pass through the same cross section of the pipe unit1110, the impurity microbe M may be detected at the same time. Inaddition, when a plurality of emission holes 1103 are provided, one ofthe emission holes 1103 may be disposed on the same circumference as anincidence position at which the first wave L11 is incident from the wavesource 1200. The emission holes 1103 except for the one emission hole1103 may be disposed on a circumference different from the wave source1200. For example, as shown, the plurality of emission holes 1103 may bedisposed on different circumferences so as not to overlap with respectto the longitudinal direction of the pipe unit 1110.

Meanwhile, the impurity detection system 10 may be capable of detectingimpurities when the impurities in the fluid are present in a certainconcentration range. The impurity detection system 10 may also perform afunction of measuring an optical density (OD) of the fluid by estimatingthe concentration of impurities in the fluid. It is difficult for ageneral OD measuring device in measuring impurity concentration of 10⁵cfu/ml or less. However, the impurity detection system 10 according toan embodiment of the present disclosure may also be capable of measuringthe impurity concentration of 10⁵ cfu/ml or les through a method ofdetermining the impurity concentration as follows. Here, impurities arenot limited to microbes. The impurity detection system 10 may be capableof detecting impurities even at 1×10° cfu/ml by the number of times ofmultiple scattering of the amplified first wave L11. In addition, theimpurity detection system 10 may be capable of detecting impurities evenwhen the impurities of the range of 9×10⁹ cfu/ml are present. When therange is converted into an OD range, the impurity detection system 10may be capable of detecting impurities in the fluid with an OD in therange of 0 to 30.

Hereinafter, for convenience of description, a method, performed by thecontroller 1400, of determining the concentration of microbes by using alaser speckle will be described mainly on the case where impurities aremicrobes.

The controller 1400 may calculate a standard deviation of lightintensity of the laser speckle on a laser speckle image measured at eachreference time. As microbes included in the fluid continuously move,constructive interference and destructive interference may change inresponse to the movement. In this case, as the constructive interferenceand the destructive interference change, a degree of light intensity maychange greatly. Then, the controller 1400 may detect the microbes bycalculating the standard deviation indicating the degree of change inthe light intensity, and measure the distribution of the microbes.

For example, the controller 1400 may synthesize the laser speckle imagemeasured at a predetermined time and calculate the standard deviation ofthe light intensity of the laser speckle over time from the synthesizedimage. The standard deviation of light intensity of the laser speckleover time may be calculated based on Equation 6 below.

$\begin{matrix}{{S\left( {x,y} \right)} = \sqrt{\frac{1}{T}{\sum\limits_{t = 1}^{T}\; \left( {{I_{t}\left( {x,y} \right)} - \overset{\_}{I}} \right)^{2}}}} & \left\lbrack {{Equation}\mspace{14mu} 6} \right\rbrack\end{matrix}$

In Equation 6, S may denote the standard deviation, (x, y) may denotecamera pixel coordinates, T may denote the total measurement time, t maydenote the measurement time, It may denote light intensity measured atthe time t, and Ī may denote a mean light intensity over time.

Constructive and destructive interference patterns vary according to themovement of the microbes, and a standard deviation value calculatedbased on Equation 6 may become large, and thus the concentration of themicrobes may be measured. However, the present disclosure is not limitedto the method of measuring the concentration of the microbes by Equation6 above, and may measure the concentration of the microbes by using anymethod using a difference of the detected laser speckle.

The controller 1400 may estimate a distribution, i.e., concentration, ofthe microbes included in the fluid based on a linear relationshipbetween the magnitude of a standard deviation value of a light intensityof a second laser speckle and the microorganism concentration.

Meanwhile, FIGS. 6A and 6B are conceptual diagrams schematically showingan impurity detection system according to another embodiment of thepresent disclosure.

Referring to FIGS. 6A and 6B, the impurity detection system may furtherinclude an optical unit 1550 restoring and modulating a first wavesignal scattered in a fluid into a second wave signal before a firstwave of the wave source 1200 is scattered by the fluid. In this case,the optical unit 1550 may include a spatial light modulator (SLM) 1551and the detector 1300. When a scattered wave is incident from ameasurement target, the optical unit 1550 may control a wavefront of thescattered wave, restore the wave to a wave (light) before beingscattered, and provide the wave to the detector 1300.

The wave (light) may be incident on the SLM 1551 from a sample. The SLM1551 may control a wavefront of the wave scattered from the sample toprovide the wave to a lens 1552. The lens 1552 may concentrate thecontrolled light and provide the light to the detector 1300 again. Thedetector 1300 may detect the wave concentrated by the lens and restoreand output the wave output from an initial wave source to be scattered.

Here, when a microbe is not present in a stable medium, that is, thefluid, the optical unit 1550 may restore the first wave signal scatteredfrom the fluid to the wave before scattered. However, when the microbe Mis present in the fluid, because the first wave signal changes due to amovement of the microbe, a phase control wavefront may not be detected,and thus the first wave signal may not be modulated into the second wavesignal having a phase conjugation wavefront. The impurity detectionsystem including the optical unit 1550 described above may estimate thepresence of impurities more finely by using a difference of the secondwave signal.

FIG. 7 is a conceptual diagram schematically showing a microbialpopulation counting system 20 according to an embodiment of the presentdisclosure. FIG. 8 is a cross-sectional view taken along line III-III ofFIG. 7.

Referring to FIGS. 7 to 8, the microbial population counting system 20according to an embodiment of the present disclosure may include asample placement unit 2100, a wave source 2200, a detector 2300, and acontroller 2400.

As used herein, the term “microbe” refers to a prokaryotic or eukaryoticmicrobe with the ability to produce useful target substances such asL-amino acids. For example, a microbe with an increased intracellularATP concentration may be a microbe belonging to Escherichia sp., Erwiniasp., Serratia sp., Providencia sp., Corynebacterium sp., Pseudomonassp., Leptospira, Salmonella sp., Brevibacteria sp., Hypomononas. sp.,Chromobacterium sp., Norcardia, fungi, or yeast. Specifically, themicrobe may be the Escherichia sp. microbe.

Alternatively, the microbe may include bacteria selected from the groupconsisting of Staphylococcus, staph Coagulase negative, Staph. Aureus,Streptococcus spp., Streptococcus viridans group, Enterococcus spp.,Corynebacterium spp., Aerococcus spp., Micrococcus spp.,Peptostreptococcus spp., Lactococcus spp., Leuconostoc spp.), Tothiaspp. Gemella spp., Alcaligenes spp., Alternaria spp., Flavobacteriumspp., Bacillus spp., Achromobacter spp., Acinetobacter spp.,Actinobacillus spp., Alcaligenes spp., Campylobacter spp., Edwardsiellaspp., Ehrlichia spp., Enterobacter spp., Ewingella spp., Flavobacteria,Hafnia spp., klebsiella, Klebsiella spp., Kluyvera spp., Legionellaspp., Morxella spp., Morganella spp., Neisseria spp., Pasteurella spp.,Prevotella spp., Proteus spp., Providencia spp., Pseudomonas spp.,Rahnella spp., Salmonella spp., serratia, Serratia spp., Shigella spp.,Sphingobacterium spp., Vibrio spp., yersinia, Yersinia spp., Neisseriaspp., Kingella spp., Cardiobacterium, NTB: non-Tuberculosismycobacteria), Mycobacterium tuberculosis, and Mycobacterium avium. Morespecifically, the microbe may be E. coli. However, the technical idea ofthe present disclosure is not limited thereto, and may further includeother microbes.

The sample placement unit 2100 may include a plurality of split cells2110 distributing and accommodating samples to be measured. In thiscase, each of the plurality of split cells 2110 may include a culturematerial 2120 for microbe culture. The culture material 2120 may includea material corresponding to a type of microbe to be counted toeffectively culture the microbe.

A medium including the culture material 2120 used for culture shouldsuitably meet the requirements of a specific microbe. Various microbeculture media are described, for example, in “Manual of Methods forGeneral Bacteriology” by the American Society for Bacteriology,Washington D.C., USA, 1981.) These media include various carbon sources,nitrogen sources and trace element components. Carbon sources mayinclude carbohydrates such as glucose, lactose, sucrose, fructose,maltose, starch and fiber; fats such as soybean oil, sunflower oil,castor oil and coconut oil; fatty acids such as palmitic acid, stearicacid and linoleic acid; alcohols such as glycerol and ethanol andorganic acids such as acetic acid, and these carbon sources may be usedalone or in combination, but are not limited thereto. Nitrogen sourcesmay include organic nitrogen sources and urea, such as peptone, yeastextract, gravy, malt extract, corn steep liquor (CSL), and bean flour,and inorganic nitrogen sources such as ammonium sulfate, ammoniumchloride, ammonium phosphate, ammonium carbonate, and ammonium nitrate,and these nitrogen sources may be used alone or in combination, but arenot limited thereto. The medium may further include potassium dihydrogenphosphate, dipotassium hydrogen phosphate, and correspondingsodium-containing salts as phosphoric acid sources, but is not limitedthereto. The medium may also include metals such as magnesium sulfate oriron sulfate, and amino acids, vitamins and suitable precursors may beadded.

In addition, in order to maintain aerobic conditions of a culturesolution, oxygen or a gas including oxygen (e.g., air) may be injectedinto the culture solution. A temperature of the culture may generally be20-45° C., specifically 25-40° C.

Here, a sample S2 may be prepared by diluting according to the dilutionratio for counting the number of colonies. In general, the number ofbacteria that may be deployed on a plate and measured separately isabout 1000 as the number of colonies of E. coli in the case of the platehaving a diameter of 10 cm. As will be described later, in the presentdisclosure, because after microbes are deployed on the plate, each ofthe microbes included in the plurality of divided cells 2110 may bedetected without forming a colony, the number of countable bacteria maybe different according to the dilution ratio of the sample S2 and/or thenumber of split cells 2110, and more bacteria may be counted than thebacteria described above.

Specifically, the plurality of split cells 2110 may be provided in theform of a matrix of (n, m), and the number thereof may be greater than apredicted microbial population included in the sample S2. As will bedescribed later, the samples S2 may equally accommodated in theplurality of split cells 2110, and may be prepared generally by dilutingaccording to a dilution ratio for counting the number of colonies. Forexample, when the plurality of split cells 2110 is provided in a matrixof (100, 100), the sample S2 may be diluted such that the microbialpopulation does not exceed 10⁴. Alternatively, when the plurality ofdivided cells 2110 is provided in a matrix of (100, 100), the sample S2may be diluted such that the microbial population does not exceed 10⁶.

Meanwhile, the sample placement unit 2100 may include a multiplescattering amplification region for amplifying the number of times awave incident on the split cell 2110 is multiply scattered in the sampleS2. For example, the sample placement unit 2100 may be formed byincluding a multiple scattering material in at least a lower region. Forexample, the multiple scattering material may include titanium oxide(TiO₂), and may reflect at least a part of the wave passing through thesample S2 and incident on the sample placement unit 2100. The multiplescattering amplification region may cause waves that are multiplyscattered from the sample S2 to reciprocate a space between the sampleS2 and the multiple scattering amplification region at least one time.

In another embodiment, the microbial population counting system 20 maybe configured such that a multiple scattering material T2 the time T2 isincluded in the culture material 2120. In FIG. 2, the culture material2120 and the sample S2 are separated from each other, but may be mixedwith the culture material 2120 when the sample S2 is accommodated in thesplit cell 2110. At this time, the multiple scattering material T2 maybe arranged to surround the microbe M to scatter the incident wave andincrease the number of times of multiple scattering.

Meanwhile, in another embodiment, the microbial population countingsystem 20 may further include a separate multiple scattering amplifier(not shown). The multiple scattering amplifier (not shown) may beprovided on a wave movement path between the wave source 2200 and thesample placement unit 2100 and/or between the sample placement unit 2100and the detector 2300 to amplify the number of times of multiplescattering of waves. When the multiple scattering amplifier (not shown)is disposed between the wave source 2200 and the sample placement unit2100, the multiple scattering amplifier may be formed in a detachablestructure to distribute the sample S2 to the sample placement unit 2100.For example, the multiple scattering amplifier (not shown) may beconfigured in a structure such as a lid. In addition, the multiplescattering amplifier (not shown) may be provided to correspond to eachof the split cells 2110, or may be formed in a structure covering theentirety of the plurality of split cells 2110.

Meanwhile, the sample placement unit 2100 may include a blocking region2110A on a side surface of each split cell 2110 to block the waveincident to each split cell 2110 not to introduce into another splitcell 2110. The microbial population counting system 20 according to anembodiment of the present disclosure sequentially irradiates waves tothe plurality of split cells 2110 and detects laser speckles emittedcorrespondingly. As will be described later, such a process shouldaccurately detect whether the microbe is present in each of theplurality of split cells 2110, and the accuracy thereof may be reduceddue to a laser speckle emitted from the split cell 2110 other than thecorresponding split cell 2110 during a rapid detection process. In orderto prevent this, the sample placement unit 2100 may include the blockingregion 2110A on the side surface of each split cell 2110, such that awave incident on the corresponding split cell 2110 may be introducedinto the other split cell 2110 so as not to cause interference. In anembodiment, the blocking region 2110A may include a metal materialhaving a reflective characteristic.

Meanwhile, in FIG. 8, only the blocking region 2110A is disposed on theside surface of the split cell 2110, but the technical idea of thepresent disclosure is not limited thereto. In another embodiment, theblocking region 2110A may also be disposed on a lower surface of thesplit cell 2110. In this case, unlike that shown in FIG. 8, the detector2300 may be disposed on an upper portion of the sample placement unit2100 to detect an emitted laser speckle. Alternatively, the detector2300 may be disposed to face the wave source 2200 with respect to thesample placement unit 2100 as shown in FIG. 7 but may detect a laserspeckle emitted through a predetermined through region of the lowersurface of the sample placement unit 2100 in which a blocking region isnot formed.

Although not shown, the sample placement unit 2100 may further include areference cell (not shown) formed in the same shape as the plurality ofsplit cells 2110 and positioned on an irradiation path of wave. At thistime, the reference cell (not shown) may have the same size as theplurality of split cells 2110 to include a culture material of the sametype and capacity. However, unlike the split cells 2110, the sample S2is not accommodated in the reference cell (not shown).

The culture material may have some degree of fluidity, which may act asnoise to detect a laser speckle according to a subtle movement of amicrobe. In this case, because the reference cell (not shown) providedin the sample placement unit 2100 together with the plurality of splitcells 2110 does not accommodate the sample S2 but includes the culturematerial, when a subtle vibration occurs in the sample placement unit2100 and thus the culture material of the plurality of split cells 2110has fluidity, the culture material of the reference cell (not shown)also has the same fluidity. The microbial population counting system 20may equally irradiate waves to the reference cell (not shown) and set alaser speckle detected therefrom as a reference value, thereby removingnoise to correctly identify the presence of the microbe in the othersplit cells 2110.

Referring to FIGS. 7 and 8 again, the wave source 2200 may sequentiallyirradiate waves to the plurality of split cells 2110 of the sampleplacement unit 2100. The wave source 2200 may apply all kinds of sourcedevice capable of generating waves, and may be, for example, a lasercapable of irradiating light of a specific wavelength band. Meanwhile,the wave source 2200 may be connected to a driving device such as amotor or an actuator to sequentially irradiate waves toward therespective split cells 2110 according to a preset time interval.Although the present disclosure is not limited to a type of a wavesource, a case where the wave source is the laser will be described forconvenience of description.

For example, laser with a good coherence may be used as the wave source2200 to form speckle in the sample S2 accommodated in the plurality ofsplit cells 2110. In this case, the shorter the spectral bandwidth ofthe wave source that determines the coherence of the laser wave source,the greater the measurement accuracy. That is, the longer the coherencelength, the greater the measurement accuracy. Accordingly, a laser lightwhose spectral bandwidth of the wave source is less than a predeterminedreference bandwidth may be used as the wave source 1200, and themeasurement accuracy may increase as the spectral bandwidth of the wavesource is shorter than the reference bandwidth.

Meanwhile, the detector 2300 may sequentially detect individual waveinformation emitted from the sample S2 accommodated in each split cell2110 in association with sequentially irradiated waves. At this time,the individual wave information may be information obtained by detectinga laser speckle generated by multiple scattered from the sample S2accommodated in each of the plurality of split cells 2110 for eachpreset time. Specifically, the individual wave information includesfirst image information of a laser speckle detected at a first time,second image information of a laser speckle detected at a second time,and third image information of a laser speckle detected at a third timeamong the laser speckles emitted from the corresponding split cell 2110,wherein the first to third times may be different times. The detector2300 may provide the controller 2400 with information about the laserspeckles detected at the first to third times with respect to the onesplit cell 2110. In this case, the first to third times are the minimumnumber of detections for the controller 2400 to analyze temporalcorrelation of the laser speckles, and the detector 2300 may detect thelaser speckles at a plurality of times more than the times.

Here, time means any moment in a continuous flow of time, and times maybe set in advance at the same time interval, but are not limitedthereto, and may be set in advance at any time interval. The detector2300 may include a sensing means corresponding to a type of the wavesource 2200. For example, when a light source of a visible lightwavelength band is used, a CCD camera which is an image capturing devicemay be used.

Specifically, when a wave is irradiated to the sample S2 accommodated inthe one split cell 2110, the incident wave may form a laser speckle bymultiple scattering.

Because the laser speckle is generated by the interference of light, ifthere is no microbe in the sample S2, a multiple scatteringamplification region may always show a constant interference patternover time. In comparison, when the microbe M is present in the sampleS2, the laser speckle may change over time by a movement of the microbeM. The detector 2300 may detect the laser speckle that changes over timefor each preset time and provide the laser speckle to the controller2400. The detector 2300 may detect the laser speckle at a speedsufficient to detect the movement of the microbe M, and for example, maydetect the laser speckle at the speed of 25 to 30 frames per second.

The controller 2400 may determine the presence of the microbe M in eachsplit cell 2110 using the detected individual wave information, andcalculate the microbial population in the sample S2 by using the numberof split cells 2110 in which the microbe M is present. Specifically, thecontroller 2400 may obtain a temporal correlation of the detected laserspeckles using the detected laser speckles and determine the presence ofthe microbe M in the corresponding split cell 2110 based on the obtainedtemporal correlation. The controller 2400 may estimate the presence ofthe microbe in each split cells 2110 in real time based on the obtainedtemporal correlation. Real time in the present specification meansestimating the presence of the microbe M within 3 seconds, preferably,it is possible to estimate the presence of the microbe M within 1second.

In an embodiment, the controller 2400 may estimate the presence of themicrobe using the laser speckles emitted from the sample S2 at differenttimes due to the wave irradiated to the one divided cell 2110. Forexample, in FIG. 7, when a first wave S12 is irradiated to a (1,1) splitcell, the controller 2400 may estimate the presence of the microbe M inthe (1,1) split cell by obtaining a temporal relation between firstlaser speckles P12 that are multiply scattered by the first wave S12 andemitted. At this time, the controller 2400 may estimate the presence ofthe microbe M by using a difference between using first imageinformation of the first laser speckle P12 detected at the first time,second image information of a first laser speckle P22 detected at thesecond time, and third image information of a first laser speckle P32detected at the third time.

Here, the first image information to the third image information may beat least one of pattern information of the laser speckle and intensityinformation of waves. Meanwhile, an embodiment of the present disclosuremay use the difference between the at least three image information ofthe laser speckles detected at different times, but may extend this touse image information of a plurality of laser speckles at a plurality oftimes. The controller 2400 may calculate a temporal correlationcoefficient between images using the image information of the laserspeckles generated for a plurality of preset times, and estimate thepresence of the microbe M in the corresponding split cell 2110 based onthe temporal correlation coefficient.

Hereinafter, a method of counting the microbial population using themicrobial population counting system 20 described above will bedescribed in detail.

FIG. 9 is a flowchart sequentially showing a method of counting amicrobial population according to an embodiment of the presentdisclosure, and FIGS. 10 and 11 are diagrams for explaining the methodof counting the microbial population.

Referring to FIGS. 9 to 11, the method of counting the microbialpopulation according to an embodiment of the present disclosure may,first, prepare the sample placement unit 2100 (S100). The sampleplacement unit 2100 may include the plurality of split cells 2110 eachincluding a culture material.

Thereafter, the sample S2 to be measured is diluted at a predetermineddilution ratio and distributed to the plurality of split cells 2110(S200). At this time, sizes of the plurality of split cells 2110 areequally configured, and the sample S2 may be uniformly distributedBecause the sample S2 is diluted such that an expected microbe Mpopulation is smaller than the number of the plurality of split cells2110, when the sample S2 is uniformly distributed, as shown in FIG. 4,the microbe M may be or may not be present in each split cell 2110.

Thereafter, waves may be sequentially irradiated to the plurality ofsplit cells 2110 by the wave source 2200, and individual waveinformation emitted from the sample S2 accommodated in each split cell2110 may be sequentially detected in association with sequentiallyirradiated waves (S300). For example, when the plurality of split cells2110 are arranged in the form of an (n, m) matrix as shown, the wavesmay be irradiated in a sequentially scanning manner along each column.At this time, the detector 2300 detects individual wave informationemitted from each split cell 2110 in association with the irradiatedwaves. As described above, the individual wave information may be aplurality of pieces of image information of laser speckles detected atdifferent times in the corresponding split cell 2110.

The controller 2400 may determine the presence of the microbe M in eachsplit cell 2110 using the detected individual wave information (S400).

For example, as shown in FIG. 4, when the microbe M is present in the(1,1) split cell and the microbe M is not present in a (2,1) split cell,the controller 2400 may define the (1,1) split cell as 1 and the (2,1)split cell as 0. Such determination of the presence of the microbe M maybe performed from the (1,1) split cell to the (n, m) split cellaccording to an irradiation path of sequential waves.

When the determination of the presence of the microbe with respect toall the split cells 2110 is completed, the controller 2400 may calculatethe microbial population in the entire samples S2 using the number ofsplit cells in which the microbe M is present. In other words, bycalculating the number of split cells defined as 1 in the entire splitcells 2110, the microbial population included in the entire samples S2may be calculated.

FIG. 12 is a conceptual diagram schematically showing a microbialpopulation counting system 20-1 according to another embodiment of thepresent disclosure.

Referring to FIG. 12, the microbial population counting system 20-1according to another embodiment of the present disclosure may furtherinclude a wave path changer 2210 in order to sequentially irradiatewaves irradiated from the wave source 2200 into the plurality of splitcells 2110. In other words, the waves are not irradiated directly to theplurality of split cells 2110 from the wave source 2200, but the wavesmay be irradiated to the plurality of split cells 2110 using the wavepath changer 2210. In another embodiment of the present disclosure,except for a method of irradiating waves, the other components are thesame as those in an embodiment, and thus redundant descriptions will beomitted for the convenience of description.

The waves may be incident on the wave path changer 2210 from the wavesource 2200. The wave path changer 2210 may be a micro mirror. The wavepath changer 2210 may include a reflective surface to reflect theincident waves toward the plurality of split cells 2110. The reflectivesurface is shown as a flat surface without refractive power, but thepresent disclosure is not limited thereto. The wave path changer 2210may be finely driven by a drive controller (not shown).

In another embodiment, the wave path changer 2210 may be finely drivenby the controller 2400, and accordingly, may sequentially irradiate thewaves to the plurality of split cells 2110. At this time, the controller2400 may also control the detector 2300 to detect the laser speckleemitted from the corresponding split cell 2110 in association with awave order irradiated by the wave path changer 2210.

The micro mirror constituting the wave path changer 2210 may employvarious configurations in which mechanical displacement of thereflective surface may occur according to electrical control. Forexample, a generally known micro electromechanical system (MEMS) mirror,a digital micromirror device (DMD) element or the like may be employed.The wave path changer 2210 is illustrated as one micro mirror, but thisis exemplary and may be a configuration in which a plurality of micromirrors are two-dimensionally arrayed.

Meanwhile, the wave path changer 2210 may further include a mirror 2215disposed on the wave path to adjust angles of the waves irradiated tothe plurality of split cells 2110 to be uniform. In other words, whenthe wave path changer 2210 irradiates the waves to the plurality ofsplit cells 2110 using the micro mirror, the incident angles of thewaves may be different according to positions of the split cells 2110.Accordingly, because a degree of multi-scattering in the sample S2 maybe different according to positions of the plurality of split cells2110, accurate comparison and evaluation may be difficult, and thus, themirror 2215 may be further disposed such to adjust the angles of thewaves irradiated to the split cells 2110 to be uniform. In the drawing,only the one mirror 2215 disposed on the (1,1) split cell isillustrated, but is schematically illustrated for convenience ofdescription, and a mirror is disposed in an upper end of each of thesplit cells 2110 such that the angles of the waves irradiated to thesplit cells 2110 may be adjusted.

FIG. 13 is a conceptual diagram schematically showing a sample placementunit 2100-1 according to another embodiment of the present disclosure.

Referring to FIG. 13, unlike the sample placement unit 2100 of anembodiment which is formed in the form of a petri dish such as an agarplate, the sample placement unit 2100-1 according to another embodimentmay be in the form of a multi-well based microfluidics chip connected toa microfluid channel 2135.

Specifically, the sample placement unit 2100-1 may include the pluralityof split cells 2110 having a multi-well shape and an injector 2130through which the samples S2 may be injected, and the plurality of splitcells 2110 and the injector 2130 may connected to the microfluidicschannel 2135. When the sample S2 is injected into the injector 2130, thesample placement unit 2100-1 may uniformly distribute the sample S2 toeach split cell 2110 through the microfluidics channel 2135.

The sample placement unit 2100-1 according to another embodiment mayinclude a culture material for culturing a microbe in each of theplurality of split cells 2110 in the same manner as in an embodiment. Inaddition, an upper surface of the sample placement unit 2100-1 mayinclude a transparent material for optical imaging. However, the presentdisclosure is not limited thereto, and as described above, a multiplescattering amplifier may be disposed on the upper surface for multiplescattering amplification.

Meanwhile, the sample placement unit 2100-1 has a blocking region on atleast a side surface of each split cell 2110 to block a wave incident toeach split cell 2110 from entering another split cell 2110. Through theblocking region, the sample placement unit 2100-1 may minimize waveinterference between the split cells 2110 to improve the accuracy of thepopulation count. In addition, the sample placement unit 2100-1 may beprovided as a disposable kit.

FIG. 14 is a diagram schematically showing an airborne bacteriameasuring device 30 according to an embodiment of the presentdisclosure, and FIG. 15 is a conceptual diagram for explaining thesampling principle of the airborne bacteria measuring device 30 of FIG.14. FIG. 16 is a block diagram of the airborne bacteria measuring device30 of FIG. 14, and FIGS. 17A to 17D are diagrams for explaining aprocess performed by the airborne bacteria measuring device 30 of FIG.14 of sampling bacteria and then processing collection liquid.

The air sampler of the related art inhales air including airbornebacteria for airborne bacteria sampling and then grows the air byspreading the air in a medium to be a measurable amount. At this time, aculture time is long, which made it difficult to detect airbornebacteria quickly.

The present disclosure is to solve the above problem, and the airbornebacteria measuring device 30 according to an embodiment of the presentdisclosure allows air in which microbes such as bacteria and germs arefloating to contact with the collection liquid, collecting the airbornebacteria in the collection liquid, and then detects the airbornebacteria using a wave speckle, and thus the airborne bacteria isdetected within a short time.

First, referring to FIGS. 14 and 15, the airborne bacteria measuringdevice 30 according to an embodiment of the present disclosure mayinclude a collection unit 3200, a wave source 3100, an image sensor3300, and a controller 3400.

The collection unit 3200 performs a function of accommodating thecollection liquid to collect the bacteria from the inhaled air.Specifically, the collection unit 3200 may include a storage tank 3201for accommodating the collection liquid W therein, an inhalation flowpath 3211 for inhaling external air to guide the external air to thecollection liquid W in one side of the storage tank 3201, and an exhaustflow path 3212 for discharging the air of the storage tank 3201 to theoutside in the other side of the storage tank 3201.

Here, the collection liquid W may be any kind of sample capable ofcollecting the bacteria through contact with the airborne bacteria. Inother words, the collection liquid W may be a liquid or a sample in theform of a gel. However, in the present disclosure, in order toaccurately detect the presence or concentration of the airbornebacteria, the collection liquid W may be prepared without includingimpurities such as microbes before contacting the air, or may bepreviously stored by in advance measuring concentration of microbesincluding impurities in the collection liquid W before contacting theair through a chaotic wave sensor that will be described later.

In an embodiment, the collection liquid W may include a liquid, and mayinclude a culture material for culturing microbes. The collection liquidW may include various microbe culture materials and is described, forexample, in “Manual of Methods for General Bacteriology” by the AmericanSociety for Bacteriology, Washington D.C., USA, 1981.) These mediainclude various carbon sources, nitrogen sources and trace elementcomponents. Carbon sources may include carbohydrates such as glucose,lactose, sucrose, fructose, maltose, starch and fiber; fats such assoybean oil, sunflower oil, castor oil and coconut oil; fatty acids suchas palmitic acid, stearic acid and linoleic acid; alcohols such asglycerol and ethanol and organic acids such as acetic acid, and thesecarbon sources may be used alone or in combination, but are not limitedthereto. Nitrogen sources may include organic nitrogen sources and urea,such as peptone, yeast extract, gravy, malt extract, corn steep liquor(CSL), and bean flour, and inorganic nitrogen sources such as ammoniumsulfate, ammonium chloride, ammonium phosphate, ammonium carbonate, andammonium nitrate, and these nitrogen sources may be used alone or incombination, but are not limited thereto. The medium may further includepotassium dihydrogen phosphate, dipotassium hydrogen phosphate, andcorresponding sodium-containing salts as phosphoric acid sources, but isnot limited thereto. The medium may also include metals such asmagnesium sulfate or iron sulfate, and amino acids, vitamins andsuitable precursors may be added.

In addition, in order to maintain aerobic conditions of the collectionliquid W, oxygen or a gas including oxygen (e.g., air) may be injectedinto the collection liquid W. A temperature of the collection liquid Wmay generally be 20-45° C., specifically 25-40° C.

At least a part of the storage tank 3201 may include a material throughwhich a wave may pass. For example, at least a region of the storagetank 3201 on which the wave is incident or from which the wave isemitted may include a material such as glass. In another embodiment,when the storage tank 3201 includes a material through which the wavemay not pass, for example, a metal material, a through holecorresponding to the region on which the wave is incident or from whichthe wave is emitted may be formed. At this time, the storage tank 3201may further include a cover portion (not shown) disposed at one side ofthe through hole. The cover portion (not shown) may include atransparent or translucent material such that the second wave L21 maypass therethrough. For example, the cover portion (not shown) mayinclude a glass or plastic material, and may be formed in a plate shapehaving flexibility, but may also be manufactured in a film. In anotherembodiment, the cover portion (not shown) may be formed to fill theinside of the through hole rather than disposed in one side of thethrough hole.

Meanwhile, the collection unit 3200 may further include a multiplescattering amplifier MS for reflecting at least a part of the wavesemitted from the collection liquid W to the collection liquid W toamplify the number of times of multiple scattering in the collectionliquid W. For example, the multiple scattering amplifier MS may scatterat least a part of the waves incident to the storage tank 3201 andscattered due to bacteria in the collection liquid W, and then emittedfrom the storage tank 3201 into the collection liquid W again. Thescattered waves may be scattered and emitted again due to the bacteriain the collection liquid W again, and the number of times of multiplescattering in the collection liquid W may increase through this process.

In an embodiment, the multiple scattering amplifier MS may be disposedbetween the storage tank 3201 and the wave source 3100, and disposedbetween the storage tank 3201 and the image sensor 3300 to reflect atleast a part of waves multiple scattered and emitted from the collectionliquid W. In other words, the multiple scattering amplifier MS may allowthe waves multiple scattered and emitted from the collection liquid W toreciprocate a space between the collection liquid W and the multiplescattering amplifier MS at least once time. The multiple scatteringamplifier MS may include a multiple scattering material, for example,the multiple scattering material may include titanium oxide (TiO₂).

In another embodiment, the collection unit 3200 may form a multiplescattering amplification region including the multiple scatteringmaterial in at least a part of the storage tank 3201. For example, themultiple scattering amplification region may be formed by coating, withthe multiple scattering material, a region corresponding to at least aspace in which the collection liquid W is accommodated in the storagetank 3201. However, the technical idea of the present disclosure is notlimited thereto, and the multiple scattering amplification region may bedisposed in the entire region of the storage tank 3201 except for thewave incidence part and emission part.

Meanwhile, the inhalation flow path 3211 may be disposed on one side ofthe storage tank 3201 and perform a function of inhaling external air toguide the external air to the collection liquid W, and the exhaust flowpath 3212 mat be disposed on the other side of the storage tank 3201 andperform a function of discharging the air of the storage tank 3201 tothe outside. As shown in the drawing, the inhalation flow path 3211 maybe formed in which one end is immersed in the collection liquid W andthe air is capable of directly contacting with the collection liquid W.However, the present disclosure is not limited thereto, and theinhalation flow path 3211 may be formed in any form capable of guidingthe external air to the collection liquid W.

Meanwhile, a filter unit 3240 may be installed in the inhalation flowpath 3211. The filter unit 3240 may perform a function of filtering asubstance having a predetermined size or more included in the externalair introduced into the inhalation flow path 3211.

The exhaust flow path 3212 may be disposed at one end of anaccommodation space of the storage tank 3201 except for the collectionliquid W so as to discharge the air of the storage tank 3201 to theoutside. The external air is guided to the collection liquid W throughthe inhalation flow path 3211, and then the remaining air excluding thecollected bacteria is discharged from the collection liquid W, and theexhaust flow path 3212 performs the function of discharging the air tothe outside. Although not shown, the collection unit 3200 may connectthe exhaust flow path 3212 with a means such as a pneumatic pump or acompressor to discharge the air in the storage tank 3201 to the outside.In addition, by generating a pressure difference of the storage tank3201 through the above-described process, the collection unit 3200 mayinhale the air into the storage tank 3201.

The collection unit 3200 may include a collection liquid flow pipe 3221for flowing the collection liquid W stored in the outside into thestorage tank 3201, and a collection liquid discharge pipe 3222 fordischarging the completely detected collection liquid W from the storagetank 3201. The collection liquid flow pipe 3221 and the collectionliquid discharge pipe 3222 may be installed at a lower portion of thestorage tank 3201 as illustrated in the drawing to facilitate theintroduction and discharge of the collection liquid W.

Meanwhile, the wave source 3100 may irradiate a wave toward thecollection liquid W of the collection unit 3200. The wave source 3100may apply all types of source device capable of generating a wave, andmay be, for example, a laser capable of irradiating light of a specificwavelength band. Although the present disclosure is not limited to atype of a wave source, a case where the wave source is the laser will bedescribed for convenience of description.

For example, laser with a good coherence may be used as the wave source3100 to form speckle in the fluid.

The image sensor 3300 may time serially measure wave speckles generatedby multiple scattered in the collection liquid W. In other words, theimage sensor 3300 may be disposed on an emission path of the wave, andmay time serially capture the waves emitted from the collection liquid Wand obtain a plurality of images. The image sensor 3300 may includesensing means corresponding to the type of the wave source 3100. Forexample, when a light source of a visible light wavelength band is used,a CCD camera which is an image capturing device may be used.

Here, each of the plurality of images may include information ofspeckles multiple scattered and generated by the bacteria due to thewaves incident on the collection liquid W. In other words, the imagesensor 3300 may detect the wave speckles generated by the irradiatedwaves multiple scattered in the collection liquid W, at a preset time.Here, time means any moment in a continuous flow of time, and times maybe set in advance at the same time interval, but are not limitedthereto, and may be set in advance at any time interval.

The image sensor 3300 may detect a first image including first speckleinformation at least at a first time and capture a second imageincluding second speckle information at a second time to control thefirst and second images to the controller 3400. Meanwhile, the firstpoint and the second point are merely one example selected forconvenience of description, and the image sensor 3300 may capture aplurality of images at a plurality of points more than the first pointand the second point. The image sensor 3300 may include a polarizer 3305in a path from which waves are emitted, thereby maximizing interferenceefficiency for speckle formation and removing unnecessary externalreflected light, etc.

The controller 3400 may detect the presence of the bacteria, that is,microbes, in the collection liquid W based on a change in the measuredwave speckles over time. In an embodiment, the controller 3400 mayobtain a temporal correlation of the wave speckles and detect thepresence of microbes in the collection liquid W based on the obtainedtemporal correlation.

Specifically, the controller 3400 may use a difference between firstimage information of a first wave speckle detected at the first time andsecond image information of a second wave speckle detected at the secondtime to detect the presence of the microbe M. Here, the first imageinformation and the second image information may be at least one ofpattern information of the wave speckle and intensity information ofwaves.

Meanwhile, an embodiment of the present disclosure does not use only thedifference between the first image information at the first time and thesecond image information at the second time but may extend this to useimage information of a plurality of wave speckles at a plurality oftimes. The controller 3400 may calculate a temporal correlationcoefficient between images using image information of wave specklesgenerated for a plurality of preset times, and estimate the presence ofthe microbe M in the collection liquid W and furthermore the presence ofthe airborne bacteria based on the temporal correlation coefficient.

Referring to FIGS. 16 and 17, the airborne bacteria measuring device 30according to an embodiment of the present disclosure may further includea sterilization unit 3500.

The sterilization unit 3500 may sterilize the collection liquid W in thestorage tank 3201. The sterilization unit 3500 may be any means capableof removing microbes in the collection liquid W. For example, thesterilization unit 3500 may include at least one of an ultraviolet (UV)lamp or a laser having a predetermined or higher output. Alternatively,the sterilization unit 3500 may sterilize using electrolysis. Meanwhile,in another embodiment, the sterilization unit 3500 does not sterilizethe collection liquid W in the storage tank 3201, but is disposed on thedischarge path of the collection liquid discharge pipe 3222 to sterilizethe discharged collection liquid W.

Meanwhile, the airborne bacteria measuring device 30 may further includea first valve 3231 installed in the collection liquid flow pipe 3221 andselectively opening and closing the collection liquid flow pipe 3221 anda second valve 3232 installed in the collection liquid discharge pipe3222 and selectively opening and closing the collection liquid dischargepipe 3222. In this case, the controller 3400 may control an operation ofthe first valve 3231 or the second valve 3232 by a preset program.

Specifically, referring to FIG. 17A, the airborne bacteria measuringdevice 30 may collect airborne bacteria M in the collection liquid Wusing the collection unit 3200. As described above, the airbornebacteria measuring device 30 may introduce the managed collection liquidW into the storage tank 3201 immediately before detection such that thecollection liquid W does not include a microbe before inhaling themicrobe M or previously measure the collection liquid W accommodated inthe storage tank 3201 to store concentration of impurities including themicrobes. When the collection liquid W stored outside is introduced intothe storage tank 3201, the controller 3400 may control the first valve3231 to be opened, after accommodating a predetermined amount of thecollection liquid W, control the first valve 3231 to be closed.Thereafter, the airborne bacteria measuring device 30 may collect thebacteria M included in the external air by contacting the inhaledexternal air with the collection liquid W.

Referring to FIG. 17B, the airborne bacteria measuring device 30 maydetect the presence or concentration of the microbe M in real time byirradiating waves in the collection liquid W, but in another embodiment,may culture the microbe M in the collection liquid W for a certainperiod of time and then detect the microbe M. When culturing the microbeM in the collection liquid W for a certain period of time and thenmeasuring the microbe M, the airborne bacteria measuring device 30 mayestimate an actual concentration of the airborne bacteria from theconcentration of the microbe M detected in consideration of the aboveperiod of time.

Referring to FIG. 17B, the completely detected collection liquid W asdescribed above may be sterilized by the sterilization unit 3500.Through this, the airborne bacteria measuring device 30 may not onlyminimize the generation of contaminants by sterilizing and thendischarging the collection liquid W but also more ultimately increasingthe accuracy of a repetitive detection process by removing microbes inthe storage tank 3201.

Referring to FIG. 17D, when the sterilization process is completed, thecontroller 3400 may control the second valve 3322 to be opened todischarge the collection liquid W in the storage tank 3201 to theoutside. By repeating the above process, the airborne bacteria measuringdevice 30 may repeatedly measure the airborne bacteria, such data may beprovided to an external server to be utilized as big data.

Hereinafter, a network environment including the airborne bacteriameasuring device 30 having the above-described configuration will bedescribed with reference to the drawings. In this regard, a method ofidentifying concentration or type of airborne bacteria as well asdetecting the airborne bacteria through machine learning will bedescribed.

FIG. 18 is a diagram showing an example of a network environment 1according to an embodiment of the present disclosure.

The network environment 1 of FIG. 18 shows the example including one ormore airborne bacteria measuring devices 30, a user terminal 2, a server3, and a network 4. FIG. 18 is an example for describing the presentdisclosure, and the number of terminals of a user and the number ofservers is not limited to that in FIG. 18.

The one or more airborne bacteria measuring devices 30 may be providedand disposed in different regions to detect airborne bacteria in eachregion through the above-described detection process. The airbornebacteria measuring device 30 may be provided to the server 3 or the userterminal 2 using the network 4 which is the communication network. Usingdata provided in this way, the server 3 may generate airborne bacteriainformation according to a region, and more specifically, anti-bacterialinformation related to the bacteria, with a map and provide the same tothe user terminal 2.

The user terminal 2 may be a fixed terminal 22 implemented as a computerdevice or a mobile terminal 21. The user terminal 2 may be a terminal ofan administrator controlling the server 3. Examples of the user terminal2 include a smart phone, a mobile phone, a navigation device, acomputer, a notebook computer, a digital broadcasting terminal, apersonal digital assistant (PDA), a portable multimedia player (PMP), atablet PC, and the like. For example, the user terminal 1 21 maycommunicate with another user terminal 22 and/or the server 3 throughthe communication network 4 using a wireless or wired communicationmethod.

The communication method is not limited and may include not only acommunication method using a communication network (e.g., a mobilecommunication network, a wired internet, a wireless internet, and abroadcasting network) that the network 4 may include, but also a shortrange wireless communication between devices. For example, the network 4may include any one or more of networks among a personal area network(PAN), a local area network (LAN), a campus area network (CAN), ametropolitan area network (MAN), a wide area network (WAN), a broadbandnetwork (BBN), and the Internet. The network 4 may also include any oneor more of network topologies, including bus networks, star networks,ring networks, mesh networks, star-bus networks, tree or hierarchicalnetworks but is not limited thereto.

The server 3 may communicate with the user terminal 2 or the airbornebacteria measuring device 30 through the network 4 to be implemented asa computer device or a plurality of computer devices providing command,code, file, content, service, etc.

The airborne bacteria measuring device 30 according to an embodiment ofthe present disclosure may perform a function of collecting the airbornebacteria through an independent configuration, measuring wave specklesemitted from a collection liquid, learning a microbial classificationcriteria using the wave speckles by the controller 3400, and detectingbacteria in the collection liquid using the learned microbialclassification criteria.

However, the technical idea of the present disclosure is not limitedthereto, the airborne bacteria measuring device 30 may transmitdetection data to the external server 3, and the external server 3 mayuse the transmitted data to machine learn the microbial classificationcriteria and provide a learned algorithm to the airborne bacteriameasuring device 30. The airborne bacteria measuring device 30 maydetect the presence of airborne bacteria or identify the concentrationor the type of the airborne bacteria using the provided algorithm anddata about newly measured wave speckles. Hereinafter, for convenience ofexplanation, the case where the server 3 machine learns the microbialclassification criteria will be mainly described.

FIG. 19 is a block diagram schematically showing the server 3 accordingto an embodiment of the present disclosure.

The server 3 may correspond to at least one processor or may include atleast one processor. Accordingly, the server 3 may be driven by includedin a hardware device such as a microprocessor or a general purposecomputer system. Here, the ‘processor’ may refer to, for example, a dataprocessing unit embedded in hardware and including a circuit physicallystructured to perform a function represented in codes or commandsincluded in a program. An example of the data processing unit embeddedin the hardware may include a processing device such as amicroprocessor, a central processing unit (CPU), a processor core, amultiprocessor, application-specific integrated circuit (ASIC), fieldprogrammable gate array (FPGA), and the like, but the scope of thepresent disclosure is not limited thereto.

The server 3 shown in FIG. 19 shows only the components related to thepresent embodiment in order to prevent the features of the presentembodiment from being blurred. Accordingly, it will be understood bythose skilled in the art that other general purpose components may befurther included in addition to the components illustrated in FIG. 19.

Referring to FIG. 19, the server 3 according to an embodiment of thepresent disclosure may include an input/output interface 31, a receiver32, a processor 33, and a memory 34.

The memory 34 is a computer readable recording medium, and may include apermanent mass storage device such as random access memory (RAM), readonly memory (ROM), and a disk drive.

The input/output interface 31 may be means for interfacing withinput/output devices. For example, the input device may include a devicesuch as a keyboard or mouse, and the output device may include a devicesuch as a display for displaying a communication session of anapplication. As another example, the input/output interface 31 may bemeans for interfacing with a device such as a touch screen in whichfunctions for input and output are integrated into one.

The receiver 32 may receive a plurality of images from the airbornebacteria measuring device 30. At this time, the plurality of images maybe images obtained by the image sensor 3300 of the airborne bacteriameasuring device 30 by capturing waves emitted from the collectionliquid W in the time series order. That is, the receiver 32 may functionas a communication module using wired or wireless communication, and mayreceive the plurality of images. At this time, the receiver 32 mayprovide a function for the user terminal 1 21 and the server 3 tocommunicate with each other over the network 4, and may provide afunction for communicating with another user terminal (e.g., the userterminal 2 22) or another server.

The processor 33 may be configured to process commands of a computerprogram by performing basic arithmetic, logic, and input/outputoperations. The command may be provided to the processor 33 by thememory 34 or the receiver 32. For example, the processor 33 may beconfigured to execute a command received according to a program codestored in a recording device such as the memory 34. The processor 33 mayinclude a learner 331, a detector 332, and a determiner 333.

The detector 322 may extract a feature of change over time from aplurality of learning images received by the receiver 32. Here, theplurality of learning images are images continuously captured at a timeinterval, and include time information between the plurality of learningimages captured in the time series order. The detector 322 may extractthe feature of change over time from the plurality of learning images.

The learner 331 may learn the microbial classification criteria foridentifying the type or the concentration of microbes present in thecollection liquid W based on the extracted feature. The learner 331learns the microbial classification criteria based on deep learning, anddeep learning is defined as a set of machine learning algorithms thatattempt high level abstractions (a job of summarizing core content orfunction in a large amount of data or complex data) through acombination of several non-linear transformation methods. The learner331 may use any one of models of deep learning, for example, deep neuralnetworks (DNNs), convolutional neural networks (CNNs), recurrent neuralnetworks (RNNs), and deep belief networks (DBNs).

In an embodiment, the learner 331 may machine learn a classificationcriterion based on temporal correlation of the received plurality oflearning images.

As described above, the plurality of learning images may includeinformation of wave speckles multiple scattered and generated from themicrobe M in the collection liquid W. As described above with referenceto FIG. 3, when bacteria are present in the collection liquid W, aspeckle may change over time due to the life activity of microbes. Inaddition, because a change of the speckle over time is differentaccording to the type or the concentration of the microbe, the learner331 may learn the microbial classification criteria for classifying thetype or concentration of the microbe using the change of the speckleover time.

FIG. 20 is a diagram for describing a method, performed by the learner331, of analyzing a temporal correlation of speckles according to anembodiment of the present disclosure.

Referring to FIG. 20, the learner 331 may calculate temporal correlationcoefficients between images as shown in Equation 3 by using imageinformation of speckles generated at a plurality of preset times, andmay learn a microbial classification criteria based on the temporalcorrelation coefficients. As shown in FIG. 20, as the concentration ofmicrobe increases, a time that the temporal correlation coefficientsfall below a reference value decreases. Using this, the concentration ofthe microbe may be analyzed through inclination values of a graphrepresenting the temporal correlation coefficients. The learner 331 maylearn the microbial classification criteria for identifying theconcentration of the microbe by analyzing the inclination values of thetemporal correlation coefficients.

FIG. 21 is a diagram showing a standard deviation distribution of thelight intensity of wave speckles measured over time.

Referring to FIG. 21, the learner 331 may calculate a standard deviationof the light intensity of speckle patterns using a plurality of learningimages measured for each reference time. As germs and microbes presentin a sample continuously move, constructive interference and destructiveinterference may change in response to the movement. At this time, asthe constructive interference and the destructive interference change, adegree of light intensity may change. The learner 331 may calculate thestandard deviation indicating the degree of change of the lightintensity, analyze locations of the germs and the microbes in thesample, and learn the distribution of the germs and the microbes.

For example, the learner 331 may calculate the standard deviation of thelight intensity of the speckle pattern detected in each of the pluralityof learning images over time. The standard deviation of the lightintensity of the speckle over time may be calculated based on Equation 6described above.

Because constructive and destructive interference change according tomovements of germs and microbes, and a value of the standard deviationcalculated based on Equation 6 is different, concentrations of germs andmicrobes may be measured based on this. The learner 331 may learn theclassification criteria based on the linear relationship between themagnitude of the standard deviation value of the light intensity of thespeckle pattern and the concentrations of germs and microbes.

Hereinafter, the case where the learner 331 learns the classificationcriteria using a CNN will be mainly described.

Here, the CNN is a type of multilayer perceptrons designed to useminimal prepocessing. The CNN may include a convolutional layer thatperforms convolution on input data, and may further include asubsampling layer that performs subsampling on an image to extract afeature map from the corresponding data. Here, the subsampling layer isa layer that increases the contrast between neighboring data and reducesan amount of data to be processed and may use max pooling, averagepooling, etc.

FIG. 22 is a diagram showing a CNN 2510 according to an embodiment ofthe present disclosure, and FIGS. 23 and 24 are diagrams for describinga convolution operation of FIG. 22.

Referring to FIGS. 22 to 24, the CNN 2510 according to an embodiment ofthe present disclosure used by the learner 331 may include a pluralityof convolutional layers A1. The learner 331 may generate an output byperforming the convolution operation between kernels and inputs of theconvolution layers.

The input of the convolutional layer is data employed as an input of thecorresponding convolutional layer and includes at least one inputfeature map corresponding to initial input data or an output generatedby a previous layer. For example, an input of the convolutional layer 1A113 shown in FIG. 8 may be a plurality of images 2501 which are initialinputs of the CNN 2510, and an input of a convolutional layer 2 A123 maybe an output 2511 of the convolutional layer 1 A113.

The input 2501 of the CNN 2510 is the plurality of C images 2501received by the receiver 32, and a temporal correlation may beestablished between images that are input feature maps. Each image, thatis, each input feature map may have a plurality of pixels includingpreviously set width W and height H. Because there are C input featuremaps, the size of the input 2501 may be expressed as W×H×C. The learner331 may perform the convolution operation corresponding to the input2501 by using one kernel corresponding to a convolution layer A1.

At least one kernel of a convolutional layer A13 is data employed forthe convolution operation corresponding to the correspondingconvolutional layer A1, and may be defined based on, for example, aninput and an output of the corresponding convolutional layer. At leastone kernel may be designed for each convolutional layer A13 constitutingthe CNN 2510. At least one kernel corresponding to each convolutionallayer may be referred to as a kernel set G600.

Here, the kernel set G600 may include kernels corresponding to outputchannels D. For example, in order to obtain a desired output of theconvolutional layer A13, the kernel set G600 of the correspondingconvolutional layer may be defined such that an input and a convolutionoperation of the corresponding convolutional layer are performed. Theoutput of the convolutional layer A13 is data based on a result of theconvolution operation between the input of the correspondingconvolutional layer and the kernel set, and may include at least oneoutput feature map and be employed as an input of a next layer.

The learner 331 may generate an output 2511 by performing theconvolution operation between the kernel set G600 corresponding to theconvolution layer A13 and the input 2501. The output 2511 of theconvolutional layer A13 may include output feature maps 25111corresponding to the D output channels, and the size of each outputfeature map 25111 may be W×H. Here, the width, height, and number(depth) of the output 2511 are W, H, and D, respectively, and the sizeof the output 2511 may be expressed as W×H×D.

For example, the kernel set G600 corresponding to the convolutionallayer A1 may include convolutional kernels corresponding to the D outputchannels. The learner 331 may generate the output feature maps 25111corresponding to the D output channels based on operation resultsbetween the input 2501 and the kernels corresponding to the D outputchannels.

The learner 331 may include the plurality of convolution layers A13, andin an embodiment, may include the 4 to 7 convolution layers A13. Forexample, as shown in the figure, the learner 331 may include 5convolution layers A113, A123, A133, A143, and A153. Through theplurality of convolution layers A113, A123, A133, A143, and A153, thelearner 331 may increase a learning capacity that may imply a complexnon-linear relationship. However, the present disclosure is not limitedthereto, and the more convolutional layers A13 may be used to learn.

Meanwhile, each of the convolution layers A13 may include an activationfunction. The activation function may be applied with respect to layersof each layer to perform a function that allows respective inputs tohave a complex non-linear relationship. The activation function may usea sigmoid function, a tanh function, a rectified linear unit (ReLU), aleaky ReLU, etc., which may convert an input into a normalized output.

The learner 331 according to an embodiment of the present disclosure maycompletely initialize the kernels by using values of −1 to 1 duringfirst learning using the CNN 2510. In the case of using the activationfunction that outputs all of data having a negative value as 0, outputvalues including valid information may not be transferred to a nextconvolution layer, which may reduce learning efficiency. Therefore, inan embodiment of the present disclosure, the learner 331 may add a leakyReLU layer after the convolutional layer A13 and output a positive valueas it is, but may output input data of a negative value to have aconstant inclination. Through this, the learner 331 may prevent theconvergence speed degradation and local minimization problems whilelearning.

The input 2501 may be a set of input feature maps to which padding isapplied, wherein padding refers to a technique of filling a partialregion of an input with a specific value. Specifically, applying paddingto the input with the pad size of 1 means an operation of filling anedge of the input feature map with the specific value and zero paddingrefers to setting the specific value to 0. For example, when zeropadding with the pad size of 1 is applied to the size input of X×Y×Z,the input to which padding is applied is data in which the edge is 0 andthe size is ((X+1)×(Y+1)×Z and may include (X+1)×(Y+1)×Z input elements.

Meanwhile, the learner 331 learns using temporal correlations of aplurality of images in performing the convolution operation with theplurality of images including speckle information as input. At thistime, each image may include a plurality of speckles that are grainshape patterns. At this time, the learner 331 may learn theclassification criteria based on a temporal correlation of each speckle.In other words, the learner 331 learns the classification criteria usingthree-dimensional information including information of time other thantwo-dimensional information of an image.

The learner 331 should concentrate on information about one speckle, andin order to accurately obtain three-dimensional information about onespeckle, should learn the classification criteria by identifying the onespeckle and surrounding speckles. Therefore, the learner 331 may performthe convolution operation using a convolution kernel having a sizesmaller than that of one speckle. That is, when the size of one specklecorresponds to m pixels, the learner 331 performs the convolutionoperation using a convolution kernel of a size of n×n smaller than m. Inan embodiment, as described above, because the image sensor 3300 isarranged such that at most 5 pixels are located in a speckle grain size,m may be 5, where n may have a value of 1. That is, the learner 331 mayperform the convolution operation using a 1×1 convolution kernel.However, the technical idea of the present disclosure is to perform theconvolution operation using a kernel having a size smaller than that ofa speckle, but the present disclosure is not limited thereto.

The kernel set G600 may include convolution kernels corresponding to theD output channels, and each convolution kernel may include kernelfeature maps corresponding to a plurality of image number. Because thesize of each kernel feature map is n×n, the kernel set G600 includesn×n×C×D kernel elements. Here, the size of the convolution kernel isn×n×C, where C may be the number of a plurality of images, that is, thenumber of image frames. The number of convolution kernels may be equalto the number C of the plurality of images. In this case, the number ofconvolution kernels may be used for Fourier transformation of the samecondition or analysis using Fourier transformation using an outputresult of each layer.

As shown in FIG. 21, the learner 331 may perform an operation between aconvolution kernel corresponding to a first output channel of the kernelset G600 and the input 2501 to generate the output feature map 25111corresponding to the first output channel. In this way, the learner 331may generate the output feature maps 25111 corresponding to the D outputchannels by performing operations between the D kernels of the kernelset G600 and the input 2501 and generate an output 252511 including thegenerated output feature maps 25111.

For example, the learner 331 may perform an operation between aconvolution kernel 600 corresponding to a D-th output channel having thesize of nxnx C and the input 501 having the size of W×H×C to generatethe output feature map 25111 of the size of W×H, and the generatedoutput feature map 25111 corresponds to the D-th output channel.Specifically, the convolution kernel 600 corresponding to the D-thoutput channel includes C kernel feature maps, and the size of eachkernel feature map is n×n. The learner 331 may slide each kernel featuremap having the size of n×n on each input feature map having the size ofW×H included in the input 501 by a specific stride to generate theoutput feature map 25111 that is the operation result between theconvolution kernel 2600 correspond to the D-th output channel and theinput 2501.

Here, the stride means an interval for sliding the kernel feature mapduring the convolution operation. As described above, in order toconcentrate on the information about one speckle, because the learner331 needs to learn the classification criteria by identifying the onespeckle and the surrounding speckles, the slid s that is the slidinginterval may have a value corresponding to the size of the convolutionkernel such that each convolution kernel and its corresponding region donot overlap. In other words, when using the convolution kernel of thesize n×n, the stride s may have a value of n. For example, in the caseof the 1×1 convolution kernel, the stride s may be 1. Through this, thelearner 331 may learn the classification criteria based on only the timeinformation of one speckle by non-overlapping one speckle and othersurrounding speckles.

In an embodiment, the learner 331 may perform the convolution operationto have the same output channel number D as the plurality of imagenumber C in learning the classification criteria using the CNN 2510. Inother words, the kernel set G600 may include D convolution kernelsincluding C kernel feature maps, where C and D may be the same.

Meanwhile, the learner 331 may reduce the size of the output 2515 usinga pooling operation after the convolution operation using theconvolution layers A1. For example, the learner 331 may reduce the sizeof the output 2515 using subsampling A2. For example, the subsamplingmay be global average pooling which is an operation of setting anaverage value within a range of a predetermined size as a representativeof the range. However, the present disclosure is not limited thereto,and may use max pooling, min pooling, etc.

Thereafter, the learner 331 may obtain a final output 2541 by applying apredetermined operation and a weight to the feature maps 2521 extractedthrough a filter of the subsampling A23, using a fully connected layer.For example, the learner 331 may further apply A33 a leaky reLU to thefully connected layer after performing the subsampling A23, and thenobtain the final output by applying A43 a softmax layer to the fullyconnected layer. Here, the final output 2541 may be microbialclassification criteria for identifying a type or a concentration ofmicrobe by the temporal correlation of the speckle.

Thereafter, the server 3 may receive an image related to a wave speckleobtained by irradiating a wave to the new collection liquid W from theairborne bacteria measuring device 30, and the determiner 333 mayidentify a type or a concentration of bacteria included in the newcollection liquid W based on the obtained microbial classificationcriteria. However, the determiner 333 does not necessarily need to beincluded in the server 3, and when the microbial classification criterialearned from the server 3 is provided to the controller 3400 of theairborne bacteria measuring device 30, the controller 340 may identifythe type or the concentration of bacteria included in the new collectionliquid W based on the microbial classification criteria, like a functionof the determiner 333.

FIG. 25 is a graph comparing predicted microbe information (prediction)obtained by measuring airborne bacteria through machine learningaccording to an embodiment of the present disclosure and actual microbeinformation (ground truth).

Referring to FIG. 25, it may be seen that a matching rate between thepredicted microbe information obtained through an airborne bacteriameasuring technology according to an embodiment of the presentdisclosure and the actual microbe information is very high. It may beconfirmed through a result of FIG. 25 that the airborne bacteriameasuring device 30 may use microbial classification criteria toidentify a type (B. subtilis, E. Coli, P. aeruginosa, S. aureus) ofmicrobe included in the collection liquid W, etc., as well as identifyeach concentration.

As described above, the airborne bacteria measuring device according tothe embodiments of the present disclosure may collect airborne bacteriain a collection liquid, and then detect the presence of microbe in thecollection liquid using a wave speckle, thereby detecting the airbornebacteria quickly and accurately without a separate chemical method. Inaddition, the airborne bacteria measuring device may obtain theclassification criteria for classifying types or concentrations ofmicrobes using a change in a temporal correlation of a speckle throughmachine learning, thereby quickly and accurately identifying a type or aconcentration of the airborne bacteria. Through this, it is possible toidentify the presence of pathogens in the air within a region, andeffectively determine regional prevention information through a networkenvironment.

FIG. 26 is a diagram schematically showing an optical detection system40 according to an embodiment of the present disclosure, FIG. 27 is adiagram for explaining a process, performed by a first specklegeneration unit 4310 of generating a first speckle LS14, and FIG. 28 isa diagram for explaining a process, performed by a second specklegeneration unit 4410 of generating a second speckle LS24.

Referring to FIG. 26, the optical detection system 40 according to anembodiment of the present disclosure may include a wave source 4100, anoptical unit 4200, a first speckle generator 4300, a sample measurer4400, and a controller 4500.

The wave source 4100 may generate a wave L4. The wave source 4100 mayapply all types of source device capable of generating a wave L, and maybe, for example, a laser capable of irradiating light of a specificwavelength band. Although the present disclosure is not limited to atype of a wave source, a case where the wave source is the laser will bedescribed for convenience of description.

For example, laser with a good coherence may be used as the wave source4100 to form speckle in a sample to be measured. In this case, theshorter the spectral bandwidth of the wave source that determines thecoherence of the laser wave source, the greater the measurementaccuracy. That is, the longer the coherence length, the greater themeasurement accuracy. Accordingly, a laser light whose spectralbandwidth of the wave source is less than a predetermined referencebandwidth may be used as the wave source 1200, and the measurementaccuracy may increase as the spectral bandwidth of the wave source isshorter than the reference bandwidth.

However, in an actual measurement environment, various environmentalvariables such as temperature exist, and properties of the wave L4generated from the wave source 4100 may change due to minute vibrationsor external factors. As an example, a wavelength of the wave L4 maychange by an ambient temperature. The change in the wave L4 may cause achange in the measurement data output from the sample. In particular, asin the present disclosure, when a change of speckle over time isdetected and is used to detect a minute life activity of microbe, itmust be sensitive to even a small change in the wave L4.

The technical idea of the present disclosure is to accurately detect theproperty change in the wave L4 due to external environmental factors, tomeasure only when it is stable using detection results, or to correctmeasurement data, thereby improving the accuracy of microbe detection.

To this end, embodiments of the present disclosure may provide the onewave L4 generated from the wave source 4100 by changing a path of thewave L4 to a first path or a second path by using the optical unit 4200or by splitting the wave L4 into a first wave L14 and a second wave L24.

At this time, the optical detection system 40 merely splits the firstwave L14 and the second wave L24 by the optical unit 4200 or changespaths but provides the same environmental condition, and thus theproperties of the first wave L14 and the second wave L24 are the same.The first wave L14 may be used as an incident wave for generating areference signal, and the second wave L24 may be used as an incidentwave for generating a measurement signal.

The optical unit 4200 may include one or more optical elements toperform a function of transferring the wave L4 generated by the wavesource 4100 to the first path or the second path. In an embodiment, theoptical unit 4200 may include an optical path changing means forproviding the wave L4 to the first path and then changing the wave L4 tothe second path. In this case, as the optical path changing means, agenerally known micro electromechanical system (MEMS) mirror, a digitalmicromirror device (DMD) element, or the like may be employed. Inanother embodiment, the optical unit 4200 may include an optical elementthat performs a function of splitting into the first wave L14 and thesecond wave L24. As shown in the drawing, the optical unit 4200 mayinclude a beam splitter that splits the incident wave L4 into the firstwave L14 and the second wave L24 to the first path and the second pathwhich are different paths. However, the present disclosure is notlimited thereto.

In another embodiment, the optical unit 4200 may further include amultiple beam reflector. The multiple beam reflector may split the waveincident from the wave source 4100 to provide the wave to a plurality ofwave paths. The multiple beam reflector may reflect waves at front andrear surfaces to provide the parallel and split first wave L14 andsecond wave L24. At this time, the beam splitter may be disposed on theplurality of wave paths provided from the multiple beam reflector andprovide the first wave L14 and the second wave L24 to the first specklegeneration unit 4310 and the sample measurer 4400, more specifically,the second speckle generation unit 4410, respectively.

In addition, the optical unit 4200 may further include a mirror forchanging the wave path provided from the wave source 4100.

Hereinafter, for convenience of description, the case where the opticalunit 4200 splits and provides the wave L4 into the first wave L14 andthe second wave L24 will be mainly described.

Referring to FIGS. 26 and 27, the first speckle generator 4300 maydetect the first speckle LS14 which is a reference signal generatedusing the first wave L14. The first speckle generator 4300 may include afirst speckle generation unit 4310 and a first image sensor 4330.

The first speckle generation unit 4310 may be disposed on a path of thefirst wave L14. The first speckle generation unit 4310 may include astatic scattering medium 311 to scatter the first wave L14 when thefirst wave L14 is incident and generate the first speckle LS14. As shownin FIG. 27, the scattering medium 311 included in the first specklegeneration unit 4310 may include scattering materials disposed in aspatially uniform position. The scattering materials may be arrangedwithout limitations on the intervals spaced apart from each other orpositions, but maintain a static state without moving in an arrangementstate. At this time, there is no limitation on a type of the scatteringmaterial 311, for example, titanium oxide (TiO₂) may be used as thescattering material.

When the first wave L14 is incident on the first speckle generation unit4310, the first wave L14 may be multiply scattered by the scatteringmedium 311 maintaining the static state, and some of the waves scatteredin a complicated path through multiple scattering may be emitted fromthe first speckle generation unit 4310. Waves emitted by passing throughvarious points of the first speckle generation unit 4310 causeconstructive interference or destructive interference with each other,and the constructive/destructive interferences of the waves generate apattern (a speckle) in grain shape.

At this time, when the first wave L14 has a uniform characteristicwithout a change in the property over time, the first speckle LS14generated by the first speckle generation unit 4310 may also form auniform pattern or pattern by the static scattering medium 311 overtime. However, when the property of the wave L4 generated from the wavesource 4100, that is, the first wave L14, changes due to the surroundingenvironment, the pattern or pattern of the first speckle LS14 changes.

The first image sensor 4330 may be disposed on a path from which thefirst speckle LS14 is emitted to detect the first speckle LS14 in timeseries order. The first image sensor 4330 may include sensing meanscorresponding to the type of the wave source 4100. For example, when alight source of a visible light wavelength band is used, a CCD camerawhich is an image capturing device may be used. When the first imagesensor 4330 is the CCD camera, the first image sensor 4330 may timeserially capture the first speckle LS14 and obtain a plurality ofimages.

Here, each of the plurality of images includes information of firstspeckles multiple scattered and generated by the scattering medium 311due to the first wave L14 incident on the first speckle generation unit4310. In other words, the first image sensor 4330 may detect the firstspeckles generated by the irradiated first wave L14 multiple scatteredin the scattering medium 311 at a preset time. Here, time means anymoment in a continuous flow of time, and times may be set in advance atthe same time interval, but are not limited thereto, and may be set inadvance at any time interval.

The first image sensor 4330 may detect a first image at least at a firsttime and capture a second image at a second time to control the firstand second images to the controller 4500. Meanwhile, the first point andthe second point are merely one example selected for convenience ofdescription, and the first image sensor 4330 may capture a plurality ofimages at a plurality of points more than the first point and the secondpoint.

Meanwhile, referring back to FIGS. 26 and 28, the sample measurer 4400may detect a measurement signal generated using the second wave L24.Here, the measurement signal may be applicable to any kind ofmeasurement signal that may be generated using the second wave L24. Inan embodiment, the measurement signal may be a signal having the sameintensity of an emitted wave. In another embodiment, the measurementsignal may be a signal including speckle information. In other words,the sample measurer 4400 may detect the second speckle LS24 which is ameasurement signal generated using the second wave L24. Hereinafter, forconvenience of description, a case where the sample measurer 4400 is asecond speckle generation unit for detecting the second speckle LS24will be mainly described. Same reference numerals are provided to thesample measurer and the second speckle generation unit.

The second speckle generation unit 4400 may include the second specklegeneration unit 4410 and a second image sensor 4430. The second specklegeneration unit 4410 may be disposed on a path of the second wave L24.The second speckle generation unit 4410 may include a sample to bemeasured to scatter the incident second wave L24 and generate the secondspeckle LS24. The sample may be any sample for detecting microbes orimpurities. For example, the sample may be a sample such as saliva,blood, or tissue collected from an individual to be measured, or may bea sample such as feces, urine, or dead skin discharged to the outside ofthe individual. Alternatively, the sample may include an organic samplecollected from an individual such as food. Meanwhile, the sample maymean the individual to be measured itself. In other words, when the foodis an individual and the presence of microbes are measured withoutdamaging the food, the food itself may be a sample. For example, anindividual such as meat packaged for sale may be a sample.

The second speckle generation unit 4410 may accommodate only the sampledescribed above, or may accommodate the sample by including a materialfor culturing microbes such as an agar plate. Alternatively, the secondspeckle generation unit 4410 may accommodate a collection means of asample together. For example, the collecting means may be prepared usinga means by which microbes may move such as a tape, a membrane, or thelike.

In another embodiment, the second speckle generation unit 4410 mayaccommodate a sample such as a fluid. At this time, the second specklegeneration unit 4410 may be a container for accommodating the fluid, ormay be a pipe unit through which the fluid may flow.

Meanwhile, the second speckle generation unit 4410 may include amultiple scattering amplification region for amplifying the number oftimes an incident second wave is multiply scattered in the sample. Forexample, the multiple scattering amplification region may be formed byincluding a multiple scattering material in a partial region on whichthe second wave is incident and a partial region from which the secondwave is emitted. For example, the multiple scattering material mayinclude titanium oxide (TiO₂), and may be formed by coating a partialregion of the second speckle generation unit 4410 on the partial regionon or from which the second wave is incident or emitted. The multiplescattering amplification region may reflect at least a part of thesecond wave emitted by passing through the sample.

In another embodiment, the second speckle generation unit 4410 mayfurther include a separate multiple scattering amplifier 401 other thanthe multiple scattering amplification region which is coated on asurface of the second speckle generation unit 4410 and integrated. Themultiple scattering amplifier 401 may be provided on a movement path ofthe second wave L24 between the wave source 4100 and the second specklegeneration unit 4410 and/or between the second speckle generation unit4410 and the second image sensor 4430 to amplify the number of times ofmultiple scattering. The multiple scattering amplifier 401 reflects atleast a part of the second wave L24 emitted from the sample to beincident on the sample again, such that the second wave L24 mayreciprocate a space between the sample and the multiple scatteringamplifier 401 at least one time, thereby effectively amplifying thenumber of times of multiple scattering of the second wave L24 in thesample.

In addition, as another embodiment, the multi-scattering amplificationregion or the multi-scattering amplifier to perform the above functionis not provided only in the second speckle generating unit 4410, butalso provided in the first speckle generating unit 4310 as well. Ofcourse, the same scattering conditions can be given to the first specklegeneration and the second speckle generation.

Meanwhile, the first image sensor 4430 may be disposed on a path fromwhich the second speckle LS24 is emitted to detect the second speckleLS24 in time series order. The second image sensor 4430 may includesensing means corresponding to a type of the wave source 4100, andshould detect speckle using the same second wave L24 as the first waveL14, and thus the second image sensor 4430 may be the same type ofsensing means as the first image sensor 4330. The second image sensor4430 may be a CCD camera, and may obtain a plurality of images bycapturing the second speckle LS24 in time series order. At this time, aprinciple for the second image sensor 4430 of obtaining the plurality ofimages is the same as that of the first image sensor 4330, and thusredundant descriptions thereof will be omitted for convenience ofdescription.

The second image sensor 4430 detects the second speckle LS24 caused bythe second wave L24, and the first image sensor 4330 detects the firstspeckle LS14 caused by the first wave L14. Here, the first wave L14 andthe second wave L24 are split from the wave L4 irradiated from the onewave source 4100 and may have the same wave properties when thesurrounding environment is the same. Therefore, when a wavelength of thefirst wave L14 changes, because a wavelength of the second wave L24 alsochanges, the present disclosure may determine a change in the propertiesof the first wave L14 and proceed with measurement by utilizing thesecond wave only in a stable state. In particular, a bacteria detectionsensor using the speckle may detect the second speckle LS24 only in astate where the first wave L14 is stable, and thus accurate measurementmay be possible.

FIG. 29 is a diagram for explaining a method, performed by thecontroller 4500 of the present disclosure, of controlling an operationof the second image sensor 4430 due to the first speckle LS14.

Referring to FIG. 29, the controller 4500 may obtain a temporalcorrelation of the first speckle LS14 using the detected first speckleLS14, and control the operation of the second image sensor 4430 based onthe obtained temporal correlation of the first speckle LS14. Morespecifically, the controller 4500 may determine a change in the propertyof the first wave L14 based on the temporal correlation of the firstspeckle LS14, and control the operation of the second image sensor 4430according to the change in the property of the first wave L14.

The controller 4500 may obtain the temporal correlation of the firstspeckle LS14 by using a plurality of images obtained from the firstimage sensor 4330. At this time, a first image obtained at a first timeand a second image obtained at a second time may include at least one ofspeckle pattern information and intensity information of waves.Meanwhile, an embodiment of the present disclosure does not use only thedifference between the first image information at the first time and thesecond image information at the second time but may extend this to useimage information of a plurality of laser speckles at a plurality oftimes.

The controller 4500 may calculate a temporal correlation coefficient ofthe first speckle LS14 using the plurality of images generated for aplurality of preset times. When the first wave L14 is stable without achange, because the first speckle LS14 generated by the staticscattering medium 311 included in the first speckle generation unit 4310has a uniform pattern, the temporal correlation coefficient of the firstspeckle LS14 may have a uniform first value. However, when the firstwave L14 is unstable due to a change in the surrounding environment,because the first speckle LS14 also changes, the temporal correlationcoefficient changes to a second value different from the first value.The controller 4500 may determine a change in the property of the firstwave L14 by using the change in the temporal correlation coefficient.

In an embodiment, the detected temporal correlation of the first waveL14 may be calculated using Equation 5 described above.

The temporal correlation coefficient may be calculated according toEquation 5, and in an embodiment, the temporal correlation coefficientof the first speckle LS14 may be expressed in a graph over time as shownin FIG. 29. As described above, when the first wave L14 is stable, forexample, as shown in the graph up to a first time t1, the temporalcorrelation coefficient maintains a preset range P1 to P2. Unlike this,when the first wave L14 is unstable, for example, as shown in the graphof the first time t1 to a fourth time t4, the temporal correlationcoefficient may be beyond the preset range.

The controller 4500 may operate the second image sensor 4430 to detectthe second speckle LS24 only when the temporal correlation coefficientcorresponds to the preset range. In other words, as shown in FIG. 29,the controller 4500 may control the second image sensor 4430 not tooperate during the first time t1 to the fourth time t4 at which thetemporal correlation coefficient of the first speckle LS14 is beyond thepreset range P1 to P2. Meanwhile, when the first wave L14 is in anunstable state, the temporal correlation coefficient may be included inthe preset range such as a second time t2 to a third time t3 of FIG. 29.

Even though the temporal correlation coefficient is temporarily includedin the preset range, because the first wave L14 is actually unstable, inthis case, the controller 4500 may calculate the temporal correlationcoefficient to a ratio at which the temporal correlation coefficient isbeyond the preset range within a predetermined time such that the secondimage sensor 4430 does not operate and determine the change in theproperty of the first wave L14.

In another embodiment, the controller 4500 may calculate the temporalcorrelation coefficient of the first speckle LS14 and use the temporalcorrelation coefficient of the first speckle LS14 to calibrate adetection signal of the second image sensor 4430. For example, thecontroller 4500 may calculate the temporal correlation coefficient ofthe first speckle LS14 and calibrate the detection signal through anequation formula such as subtraction or division, etc. of the temporalcorrelation coefficient from the detection signal provided from thesecond image sensor 4430. The controller 4500 may detect microbes moreaccurately by using the calibrated detection signal, that is, thecalibrated second speckle LS24.

The controller 4500 may obtain a temporal correlation of the secondspeckle LS24 detected using the second speckle LS24 detected by thesecond image sensor 4430, and estimate the presence or concentration ofmicrobe in a sample based on the obtained temporal correlation of thesecond speckle.

Principle of estimating the presence or the concentration of the microbebased on the temporal correlation of the second speckle LS24 may be alsothe same as the principle of determining the change in the property ofthe first wave L14 by using the temporal correlation of the firstspeckle LS14.

Specifically, a temporal correlation coefficient of the second speckleLS24 may be calculated according to Equation 3, and in an embodiment,the presence or the concentration of microbe may be estimated through ananalysis in which the temporal correlation coefficient falls below apreset reference value. Specifically, it may be estimated that microbeis present from that the temporal correlation coefficient falls belowthe reference value exceeding a preset error range. Also, as theconcentration of microbe increases, a time that the temporal correlationcoefficients fall below a reference value decreases. Using this, theconcentration of microbe may be estimated through inclination values ofa graph representing the temporal correlation coefficient. The referencevalue may be different according to a type of microbe.

FIG. 30 is a diagram schematically showing an optical detection system40-2 of another embodiment.

Referring to FIG. 30, the optical detection system 40-2 may include thewave source 4100, the first optical unit 4200, the first specklegeneration unit 4310, the second speckle generation unit 4410, the firstimage sensor 4330, the second image sensor 4430, and the controller4500.

In another embodiment, the first speckle generation unit 4310 of theoptical detection system 40-2 may be integrally formed with the secondspeckle generation unit 4410. Specifically, the second specklegeneration unit 4410 may be an accommodation container for accommodatinga sample to be measured, and the first speckle generation unit 4310 maybe provided in one side of the accommodation container. For example, thefirst speckle generation unit 4310 may be formed in a container of apredetermined shape including a static scattering medium, and may bemounted on one side of the second speckle generation unit 4310. However,the present disclosure is not limited thereto, and in anotherembodiment, the first speckle generation unit 4410 may be formed bycoating the scattering medium fixed to one side of the second specklegeneration unit 4310.

In the optical detection system 40-2, because the first specklegeneration unit 4310 and the second speckle generation unit 4410 areintegrally formed, the first speckle L514 measured through the firstspeckle generation unit 4310 may include information about mechanicalvibration of the integrally formed second speckle generation unit 4410.Therefore, the optical detection system 40-2 may remove noise due to themechanical vibration of the second speckle generation unit 4410 througha reference signal by the first speckle LS14.

FIG. 31 is a diagram schematically showing an optical detection system40-3 according to another embodiment of the present disclosure.

Referring to FIG. 31, the optical detection system 40-3 according toanother embodiment of the present disclosure may include the wave source4100, the first optical unit 4200, the first speckle generation unit4310, the second speckle generation unit 4410, the image sensor 430, andthe controller 4500. In addition, the optical detection system 40-3according to another embodiment of the present disclosure may include afirst shutter 4350 and a second shutter 4450. Except that the opticaldetection system 40-3 according to another embodiment of the presentdisclosure controls detection of the second speckle LS24 using thesecond shutter 4450, the remaining components of the optical detectionsystem 40-3 according to another embodiment of the present disclosureare the same as those of the optical detection system 40 according to anembodiment, and thus the same reference numerals are used forconvenience of description, and redundant descriptions will be omitted.

The wave source 4100 may generate the wave L4. The wave source 4100 mayapply all kinds of source device capable of generating the wave L, andmay be, for example, a laser capable of irradiating light of a specificwavelength band.

The first optical unit 4200 may include one or more optical elements toperform a function of splitting the wave L4 generated by the wave source4100 into the first wave L14 and the second wave L24. In an embodiment,as shown in the drawing, the optical unit 4200 may include a beamsplitter that splits the incident wave L4 into the first wave L14 andthe second wave L24 to the first path and the second path which aredifferent paths.

A path of the first wave L14 provided from the first optical unit 4200may be changed to the first speckle generation unit 4310 through a firstmirror 4320. In addition, a path of the second wave L24 provided fromthe first optical unit 4200 may be changed to the second specklegeneration unit 4410 through a second mirror 4420. However, the presentdisclosure is not limited thereto and may use any means capable ofchanging a light path.

The first speckle generation unit 4310 may be disposed on the path ofthe first wave L14. The first speckle generation unit 4310 may include astatic scattering medium 311 to scatter the first wave L14 when thefirst wave L14 is incident and generate the first speckle LS14.

The second speckle generation unit 4410 may be disposed on the path ofthe second wave L24. The second speckle generation unit 4410 may includea sample to be measured to scatter the incident second wave L24 andgenerate the second speckle LS24.

The image sensor 430 may detect the first speckle LS14 generated fromthe first speckle generation unit 4310 or the second speckle LS24generated from the second speckle generation unit 4410 in time seriesorder. The image sensor 430 may be provided in an independently drivencomponent like the optical detection system 40 according to anembodiment, but the first speckle LS14 or the second speckle LS24 may bedetected by using one. To this end, the optical detection system 40-2according to another embodiment, as shown in FIG. 31, may furtherinclude a second optical unit 4210 that changes paths of the firstspeckle LS14 and the second speckle LS24 and provide the first speckleLS14 and the second speckle LS24 to the image sensor 430.

Meanwhile, the second shutter 4450 may be disposed between the firstoptical unit 4200 and the second speckle generation unit 4410 and mayoperate under the control of the controller 4500.

The controller 4500 may obtain a temporal correlation of the firstspeckle LS14 by using the first speckle LS14 detected by the imagesensor 430 and control an operation of the second shutter 4450 based onthe obtained temporal correlation of the first speckle LS14.Specifically, the controller 4500 may calculate a temporal correlationcoefficient of the first speckle LS14 and open the second shutter 4450such that the second speckle LS24 is detected only when the temporalcorrelation coefficient corresponds to a preset range. That is, thecontroller 4500 may detect the second speckle LS24 by opening the secondshutter 4450 only when it is determined that the first wave L14 isstable.

In this case, the optical detection system 40-2 may further include thefirst shutter 4350 disposed between the first optical unit 4200 and thefirst speckle generation unit 4310. Because the optical detection system40-2 according to another embodiment detects the first speckle LS14 orthe second speckle LS24 using the one image sensor 430, the controller4500 may close the first shutter 4350 such that the first speckle LS14is not detected while the image sensor 430 detects the second speckleLS24.

The controller 4500 may calculate the temporal correlation coefficientof the first speckle LS14, use the same to open the second shutter 4450,detect the second speckle LS24 for a predetermined time, and thenperiodically monitor a change in the first wave L14 by closing thesecond shutter 4450 again and opening the first shutter 4350.

FIGS. 32A and 32B are diagrams for explaining a method of determiningthe presence of live bacteria in a measurement sample using an opticaldetection system according to embodiments of the present disclosure.

In the optical detection system according to an embodiment of thepresent disclosure, a control group sample may be placed in a firstspeckle generation unit 4310′ and a measurement group sample may beplaced in a second speckle generation unit 4410′ to derive the presenceof live bacteria in a sample or a ratio of live and dead bacteria byusing detected speckle information.

Specifically, the first speckle generation unit 4310′ may include thecontrol group sample. Here, the control group sample may be a sampleprepared by injecting a sample to be measured into phosphate bufferedsaline (PBS). The control group sample may include microbes having afirst concentration, and is injected into the PBS, and thus both liveand dead bacteria in microbes do not grow over time.

The second speckle generation unit 4410′ may include the measurementgroup sample and a medium. Here, the medium may include a culturematerial for culturing microbes, and the culture material may include amaterial corresponding to a type of microbe to be identified and capableof effectively culturing the microbe.

The medium including the culture material used for culturing shouldsuitably meet the requirements of a specific microbe. Various microbeculture media are described, for example, in “Manual of Methods forGeneral Bacteriology” by the American Society for Bacteriology,Washington D.C., USA, 1981.) These media include various carbon sources,nitrogen sources and trace element components. Carbon sources mayinclude carbohydrates such as glucose, lactose, sucrose, fructose,maltose, starch and fiber; fats such as soybean oil, sunflower oil,castor oil and coconut oil; fatty acids such as palmitic acid, stearicacid and linoleic acid; alcohols such as glycerol and ethanol andorganic acids such as acetic acid, and these carbon sources may be usedalone or in combination, but are not limited thereto. Nitrogen sourcesmay include organic nitrogen sources and urea, such as peptone, yeastextract, gravy, malt extract, corn steep liquor (CSL), and bean flour,and inorganic nitrogen sources such as ammonium sulfate, ammoniumchloride, ammonium phosphate, ammonium carbonate, and ammonium nitrate,and these nitrogen sources may be used alone or in combination, but arenot limited thereto. The medium may further include potassium dihydrogenphosphate, dipotassium hydrogen phosphate, and correspondingsodium-containing salts as phosphoric acid sources, but is not limitedthereto. The medium may also include metals such as magnesium sulfate oriron sulfate, and amino acids, vitamins and suitable precursors may beadded.

In an embodiment, the measurement group sample may be the same sample asthe control group sample, and may be a sample having the sameconcentration as the control group sample. At this time, because themeasurement group sample is injected to the medium including the culturematerial, population of live bacteria may increase due to the culturematerial over time. In other words, as time passes, because the controlgroup sample is injected into the PBS, the population of live and deadbacteria remains constant, whereas the measurement group sample isinjected into the medium and the population of live bacteria increases,and thus the concentration of the measurement group sample is higherthan the concentration of the control group sample.

The controller 4500 may use the first speckle LS14 and the secondspeckle LS24 detected from the first speckle generation unit 4310′ andthe second speckle generation unit 4410′ to estimate a firstconcentration of the control group sample and a second concentration ofthe measurement group sample, and determine the presence of livebacteria in the measurement group sample using the first concentrationand the second concentration. Specifically, the controller 4500 mayobtain a temporal correlation of the first speckle LS14 using thedetected first speckle LS14, and then estimate the first correlation ofthe control group sample by using the temporal correlation of the firstspeckle. In addition, the controller 4500 may obtain a temporalcorrelation of the second speckle LS24 using the detected second speckleLS24, and then estimate the second correlation of the measurement groupsample by using the temporal correlation of the second speckle. Thecontroller 4500 may compare the estimated first concentration and secondconcentration to determine the presence of live bacteria in themeasurement group sample.

On the other hand, in another embodiment, the measurement group samplemay be a sample diluted m times the control group sample. In otherwords, the measurement group sample may have a concentration of 1/m ofthe control group sample when the measurement group sample is initiallyinjected. As shown in FIG. 32A, the control group sample is included inthe PBS, even if a certain time passes, the population of live bacteriab and dead bacteria a of the control group sample does not change.However, as shown in FIG. 32B, in the measurement group sample includedin the medium, if a certain time passes, the population of the deadbacteria a of the measurement group sample does not change, but thepopulation of the live bacteria b increases.

The controller 4500 may estimate the first concentration of the controlgroup sample using the continuously detected first speckle L514, andestimates the second concentration of the measurement group sample usingthe detected second speckle LS24, and obtain a growth time t at whichthe second concentration is equal to the first concentration. Thecontroller 4500 may derive the ratio of the live bacteria b and the deadbacteria a in the measurement group sample using the growth time t.

In other words, when the live bacteria b and the dead bacteria a arepresent in the control group sample at the first concentration as shownin FIG. 32A, the live bacteria b and the dead bacteria a are present ata concentration of 1/m in the measurement group sample obtained bydiluting this by m times, and then may be expressed as shown in Equation7 below after the growth time t.

$\begin{matrix}\frac{a - {\left( {1 - {\alpha \; t}} \right)b}}{m} & \left\lbrack {{Equation}\mspace{14mu} 7} \right\rbrack\end{matrix}$

Here, α denotes a growth rate of the corresponding microbe and may be apreviously known value.

The controller 4500 may obtain the growth time t at which the firstconcentration of the control group sample and the second concentrationof the measurement group sample are equal to each other. Thus, a ratiob/a of the live bacteria b and the dead bacteria a may be derivedthrough a process of Equation 8 below.

$\begin{matrix}{{{a - b} = \frac{a - {\left( {a - {\alpha \; t}} \right)b}}{m}}{\frac{b}{a} = \frac{m - 1}{\left( {1 - {\alpha \; t} - m} \right)}}} & \left\lbrack {{Equation}\mspace{14mu} 8} \right\rbrack\end{matrix}$

As described above, the optical measuring device according to theembodiments of the present disclosure may split a wave generated from awave source, irradiate a split first wave to a static scattering mediumto generate a first speckle that is a reference signal, and thencalculate a temporal correlation of the first speckle, therebyaccurately determining a change in properties of the first wave. Byusing this, the optical measuring device may check and calibrate noisecaused by the surrounding environment, thereby more accurately detectingmicrobe in a sample to be measured. In addition, the optical measuringdevice has the advantage of deriving the presence of live bacteria or aratio of live bacteria and dead bacteria in a sample by comparing theconcentration of a control group sample and a measurement group sample.

The embodiments have been described above. It will be understood bythose of ordinary skill in the art that various changes in form anddetails may be made therein without departing from the spirit and scopeof the present disclosure as defined by the appended claims. Therefore,it should be understood that the embodiments are to be considered in anillustrative rather than a restrictive sense. The scope of the presentdisclosure is set forth in the appended claims rather than the foregoingdescription and should be interpreted as including all differenceswithin the equivalent range thereto.

INDUSTRIAL APPLICABILITY

According to an embodiment of the present disclosure, an opticaldetection system using a chaotic wave sensor is provided. In addition,embodiments of the present disclosure may be applied to an industriallyused impurity or microbe detection device.

1. A pipe unit comprising: a body portion comprising a first crosssection, a second cross section facing the first cross section, and aninner surface penetrating the first cross section and the second crosssection to form an inner space, wherein the inner surface of the bodyportion comprises a multiple scattering amplification region in which isformed a pattern for amplifying the number of times a first waveincident between the first cross section and the second cross section ina fluid located in the inner space is multiply scattered, and whereinthe pattern is formed by arranging a plurality of grooves having apreset depth d from the inner surface at a preset interval A.
 2. Thepipe unit of claim 1, wherein the depth d and the interval Λ of thepattern are determined based on a wavelength λ of the first wave.
 3. Thepipe unit of claim 2, wherein the depth d of the pattern is determinedto satisfy the following equation: ${\frac{\lambda}{2*n} \leq d},$wherein n is a refractive index of the fluid.
 4. The pipe unit of claim2, wherein the interval Λ of the pattern is determined to satisfy thefollowing equation:${\frac{1}{\Lambda} = \frac{\sin \; \theta}{\lambda}},$ wherein θdenotes a scattering angle of the first wave scattered by the pattern.5. The pipe unit of claim 1, wherein the body portion comprises one ormore emission holes configured to guide a second wave emitted by beingmultiple scattered in the fluid to a detector.
 6. The pipe unit of claim5, wherein when two or more emission holes are formed, the two or moreemission holes are arranged at different positions of the body portion.7. An impurity detection system comprising: a pipe unit comprising abody portion formed with an inner space penetrating through a firstcross section and a second cross section such that a fluid introducedthrough the first cross section is discharged through the second crosssection and a multiple scattering amplification region configured toamplify the number of times a first wave incident between the firstcross section and the second cross section in a fluid located in theinner space is multiply scattered; a wave source configured to irradiatethe first wave toward the fluid of the pipe unit; a detector arrangedoutside the pipe unit and configured to detect a laser speckle generatedby multiple scattering of the irradiated first wave in the fluid foreach preset first time and a controller configured to obtain a temporalcorrelation of the detected laser speckle using the detected laserspeckle and estimate the presence of impurities in the fluid in realtime based on the obtained temporal correlation, wherein one or moreemission holes, configured to guide a second wave emitted by beingmultiply scattered in the fluid to the detector, are formed in the bodyportion of the pipe unit.
 8. The impurity detection system of claim 7,wherein the body portion comprises an inner surface surrounding theinner space, wherein the multiple scattering amplification region isprovided in the inner surface of the body portion and formed with apattern for amplifying the number of times the first wave is multiplyscattered, and wherein the pattern is formed by arranging a plurality ofgrooves having a preset depth d from the inner surface at a presetinterval Λ.
 9. The impurity detection system of claim 8, wherein thedepth d and the interval Λ of the pattern are determined based on awavelength λ of the first wave.
 10. The impurity detection system ofclaim 9, wherein the depth d of the pattern is determined to satisfy thefollowing equation: ${\frac{\lambda}{2*n} \leq d},$ wherein n is arefractive index of the fluid.
 11. The impurity detection system ofclaim 9, wherein the interval Λ of the pattern is determined to satisfythe following equation:${\frac{1}{\Lambda} = \frac{\sin \; \theta}{\lambda}},$ wherein θdenotes a scattering angle of the first wave scattered by the pattern.12. The impurity detection system of claim 7, wherein the second waveemitted from the one or more emission holes has a power range of 1mW/cm² or more in order for the detector to detect the laser speckle ata preset measurement speed or more.
 13. The impurity detection system ofclaim 12, wherein the measurement speed of the detector is set such thata time for the fluid to pass through the one or more emission holes isgreater than a time between first times.
 14. The impurity detectionsystem of claim 7, wherein when two or more emission holes are formed,the two or more emission holes are arranged at different positions alonga circumferential direction of the body portion, and the detector isprovided to correspond to the number of the two or more emission holes.15. The impurity detection system of claim 7, wherein the first wave hasa wavelength range of 200 nm to 1.8 μm.